Free Anti-Detect Browser Options 2026: Complete Comparison

Not everyone needs a paid anti-detect browser — several quality options offer free tiers with enough profiles for small-scale multi-account operations. This guide compares all free anti-detect browser options available in 2026, their limitations, and when to upgrade.

Free Tier Comparison

Browser	Free Profiles	Fingerprint Quality	Proxy Support	API	Team	Cookie Import
Dolphin Anty	10	Good	Yes	No	No	Yes
Incogniton	10	Good	Yes	No	No	Yes
GoLogin	3	Very Good	Yes	No	No	Yes
AdsPower	2	Good	Yes	No	No	Yes
Multilogin	0	N/A	N/A	N/A	N/A	N/A

Dolphin Anty Free — 10 Profiles

Best for: Affiliates and media buyers starting out

Feature	Free Plan	Paid (Base)
Profiles	10	100
Browser engine	Anty Browser (Chromium)	Same
Fingerprint protection	Full	Full
Cookie Robot	Manual only	Scheduled
Profile sharing	No	Yes (10 members)
API access	No	Yes
Price	$0	$89/month

Strengths: Most generous free tier for affiliates, good fingerprint engine, Chromium-based.

Limitations: No team sharing, no Cookie Robot scheduling, no API, no automation scenarios.

Incogniton Free — 10 Profiles

Best for: Budget-conscious operators who need maximum free profiles

Feature	Free (Starter)	Paid (Entrepreneur)
Profiles	10	50
Browser engine	Chromium	Same
Fingerprint	Full protection	Full
Bulk creation	Yes	Yes
Team features	No	Yes
API	No	Yes
Price	$0	$29.99/month

Strengths: 10 free profiles with full features, competitive paid upgrade pricing.

Limitations: Smaller community, less frequent updates than market leaders.

GoLogin Free — 3 Profiles

Best for: Users who want the highest fingerprint quality for free

Feature	Free	Paid (Professional)
Profiles	3	100
Browser engine	Orbita (Chromium)	Same
Fingerprint quality	Excellent	Excellent
Android app	Yes	Yes
Cloud sync	Basic	Full
API	No	Yes
Price	$0	$49/month

Strengths: Best fingerprint engine among free options, mobile app, good UX.

Limitations: Only 3 profiles limits practical usage significantly.

AdsPower Free — 2 Profiles

Best for: Testing RPA automation before committing

Feature	Free	Paid (Base)
Profiles	2	10
Browser engines	Sun (Chrome) + Flower (Firefox)	Same
RPA	Limited	Full
Fingerprint	Full	Full
Team	No	No
Price	$0	$5.4/month

Strengths: Built-in RPA even on free, dual browser engines, cheapest paid upgrade.

Limitations: Only 2 profiles, very limiting for real operations.

Choosing the Right Free Browser

Your Situation	Best Free Choice	Why
Just evaluating anti-detect	GoLogin (3 profiles)	Best fingerprint, easiest to learn
Affiliate marketing start	Dolphin Anty (10 profiles)	Most profiles, affiliate-focused
Budget multi-accounting	Incogniton (10 profiles)	10 profiles, good upgrade price
Want automation features	AdsPower (2 profiles)	RPA included, cheapest upgrade
Need maximum profiles free	Dolphin Anty or Incogniton	Both offer 10 free

When to Upgrade from Free

Signal	Action
Need more than 10 profiles	Upgrade to paid plan
Need team collaboration	Upgrade (all free tiers are solo)
Need API automation	Upgrade to plan with API access
Need Cookie Robot scheduling	Upgrade Dolphin Anty
Revenue justifies cost	Upgrade for reliability and support

Upgrade Price Comparison (100 Profiles)

Browser	100-Profile Plan	Price/Month	Cost/Profile
Multilogin X	Solo (100)	EUR 29	EUR 0.29
AdsPower	Pro (100)	$30	$0.30
GoLogin	Professional (100)	$49	$0.49
Dolphin Anty	Base (100)	$89	$0.89
Incogniton	Professional (150)	$79.99	$0.53

DIY Alternatives (Not Recommended)

Some users try free alternatives to anti-detect browsers:

Alternative	Why Not Recommended
Multiple Chrome profiles	No fingerprint spoofing, same canvas/WebGL
Incognito mode	No fingerprint protection, no persistence
Free VPNs	No fingerprint change, shared IPs, slow
VMs (VirtualBox)	Resource-heavy, no fingerprint management
Regular browser + proxy	IP changes but fingerprint stays same

These approaches leave your browser fingerprint unchanged, which platforms use alongside IP to detect multi-accounting.

Internal Linking

Incogniton Tutorial — 10 free profiles guide
GoLogin Tutorial — best free fingerprint
AdsPower Tutorial — free RPA
Dolphin Anty Tutorial — 10 free profiles
Best Anti-Detect Browsers 2026 — full paid comparison

FAQ

Are free anti-detect browsers safe to use?

Yes, the free tiers from established providers (Dolphin Anty, GoLogin, AdsPower, Incogniton) are safe. They use the same fingerprint protection as paid plans — the limitations are in profile count, team features, and automation, not security. Avoid unknown “free” anti-detect browsers from unverified sources, which may contain malware.

Can I manage real business accounts with free anti-detect browsers?

For 2-10 low-to-medium value accounts, free tiers work fine. The fingerprint protection is identical to paid plans. However, for high-value accounts (Amazon seller accounts with significant revenue, ad accounts with large budgets), upgrade to a paid plan for API access, better support, and team features that provide additional security.

Which free browser has the best fingerprint protection?

GoLogin’s Orbita engine consistently scores highest on fingerprint detection tests (CreepJS, Pixelscan, BrowserLeaks) among free options. However, all four major free options provide adequate protection for most use cases. The difference in fingerprint quality between them is smaller than the difference between any of them and using a regular browser.

Can I combine multiple free anti-detect browsers?

Technically yes — you could use 10 profiles from Dolphin Anty, 10 from Incogniton, 3 from GoLogin, and 2 from AdsPower for 25 total free profiles. However, managing profiles across four different applications is complex and error-prone. If you need 25+ profiles, upgrading to one paid plan ($29-49/month) is more practical and efficient.

Will free anti-detect browsers always stay free?

The free tiers from established providers have been stable for years and serve as user acquisition channels for paid plans. They are unlikely to be removed. However, the specific limits (number of free profiles) may change. Do not build a business entirely dependent on free tier availability — budget for paid tools as your operation grows.

Best Indonesia Proxies 2026: Residential, Datacenter & Mobile

Indonesia is Southeast Asia’s largest economy and the world’s fourth most populous country with over 275 million people. Its digital market is booming, driven by platforms like Tokopedia (now part of GoTo), Shopee Indonesia, Bukalapak, and super-apps like Gojek and Grab. With internet penetration exceeding 75% and a massive mobile-first user base, Indonesian proxies are essential for businesses looking to tap into this high-growth market. This guide covers the best Indonesian proxy solutions for 2026.

Why You Need Indonesian Proxies

Indonesia’s digital ecosystem is mobile-first and highly localized:

Monitor Indonesian e-commerce — Track pricing on Tokopedia, Shopee Indonesia, Bukalapak, Blibli, and Lazada Indonesia
Access geo-restricted content — Indonesian streaming platforms like Vidio and regional Netflix content require Indonesian IPs
Track Indonesian search results — Google.co.id shows location-specific results for the Indonesian market
Scrape ride-hailing and delivery data — Gojek, Grab, and ShopeeFood data is accessible only from Indonesian IPs
Monitor Indonesian social media — Indonesia is one of the world’s largest markets for Instagram, TikTok, and YouTube
Verify ad campaigns — Ensure digital advertisements display correctly across Indonesian cities and islands

Types of Indonesian Proxies Available

Residential Proxies

Indonesian residential proxies use IPs from local ISPs like Telkom Indonesia (IndiHome), XL Axiata, Indosat Ooredoo, and First Media. These appear as genuine Indonesian internet users, essential for accessing platforms that geo-block foreign IPs.

Datacenter Proxies

Datacenter proxies hosted in Jakarta and other Indonesian cities offer high speeds for bulk data collection. However, Indonesian platforms are increasingly blocking datacenter IP ranges.

Mobile Proxies

Indonesian mobile proxies route through 4G/5G networks from Telkomsel, XL Axiata, Indosat Ooredoo, and Tri (3). Given Indonesia’s mobile-first internet usage, mobile proxies are particularly effective for accessing mobile-optimized platforms.

ISP Proxies

Static residential proxies from Indonesian ISPs provide stable connections with residential trust levels, suitable for long-running sessions on Indonesian platforms.

Top 5 Indonesian Proxy Providers

Provider	Indonesian IP Pool	Price (per GB)	Speed Rating	Proxy Types
Bright Data	800K+ residential	$8.40/GB	★★★★★	Residential, DC, Mobile, ISP
Oxylabs	600K+ residential	$8.00/GB	★★★★☆	Residential, DC, Mobile, ISP
Smartproxy	300K+ residential	$7.00/GB	★★★★☆	Residential, DC, Mobile
IPRoyal	200K+ residential	$5.50/GB	★★★☆☆	Residential, DC, Mobile
Soax	250K+ residential	$6.99/GB	★★★★☆	Residential, Mobile

Bright Data

Bright Data maintains the largest Indonesian residential IP pool with targeting across Jakarta, Surabaya, Bandung, Medan, and other major cities. Their network handles Indonesian e-commerce platforms effectively.

Oxylabs

Oxylabs provides enterprise-grade Indonesian proxies with strong performance on Tokopedia, Shopee, and other Indonesian platforms. Their Web Unblocker handles anti-bot measures common on Indonesian sites.

Smartproxy

Smartproxy offers competitively priced Indonesian proxy coverage, suitable for small to medium businesses conducting market research in the Indonesian market.

IPRoyal

IPRoyal provides budget-friendly Indonesian proxies with both rotating and sticky session options, ideal for smaller scraping projects.

Soax

Soax delivers clean Indonesian residential and mobile proxies with real-time validation, ensuring high success rates on Indonesian platforms.

Indonesia-Specific Use Cases

Indonesian E-Commerce Intelligence

Indonesia’s e-commerce market is one of the fastest growing in the world. Monitor product pricing, seller data, and promotions across Tokopedia, Shopee Indonesia, Bukalapak, Blibli, and Lazada Indonesia. Indonesian proxies ensure you see local pricing in Indonesian rupiah (IDR) with accurate shipping costs and regional promotions.

Ride-Hailing and Super-App Data

Gojek and Grab dominate Indonesia’s ride-hailing, food delivery, and digital payments landscape. Their platforms are mobile-first and heavily geo-restricted. Indonesian mobile proxies allow you to collect pricing data, restaurant listings, and service availability across different Indonesian cities.

Social Media Market Research

Indonesia ranks among the top countries globally for Instagram, TikTok, and YouTube usage. Use Indonesian proxies to monitor trends, influencer content, and brand mentions from an Indonesian user perspective. Learn about proxies for social media.

Indonesian Property and Classifieds

Platforms like OLX Indonesia, Rumah123, and Rumah.com contain valuable real estate and classifieds data. Indonesian residential proxies help you scrape property listings and pricing trends across the Indonesian archipelago.

Travel and Hospitality Data

Indonesia is a major tourism destination, from Bali to Jakarta. Scrape hotel pricing, flight data from domestic carriers like Garuda Indonesia and Lion Air, and tourism-related content that shows different pricing to Indonesian residents. See our travel scraping guide.

Legal Considerations

Indonesia has evolving digital regulations:

Proxy usage — Using proxies is not explicitly illegal in Indonesia, but circumventing government-mandated blocks may violate regulations
UU PDP (Law No. 27/2022) — Indonesia’s Personal Data Protection Law, modeled after GDPR, governs personal data collection and processing
GR 71/2019 — Government Regulation on Electronic System and Transaction Operations requires electronic system operators to register with the government
Kominfo oversight — The Ministry of Communication and Information Technology (Kominfo) regulates internet content and has blocked numerous websites
Content blocking — Indonesia blocks access to certain websites and platforms, and Indonesian proxies will reflect these same restrictions
Data localization — Some regulations require Indonesian user data to be stored on local servers

Consult legal counsel before conducting large-scale data collection in Indonesia.

Setup Instructions

Step 1: Choose Your Provider

For Indonesian e-commerce and super-app scraping, residential or mobile proxies are strongly recommended. Most major platforms detect and block datacenter IPs.

Step 2: Configure Proxy Settings

Host: id.proxy-provider.com
Port: 10000
Username: your_username
Password: your_password

For city-level targeting:

Host: id-jakarta.proxy-provider.com (Jakarta)
Host: id-surabaya.proxy-provider.com (Surabaya)
Host: id-bandung.proxy-provider.com (Bandung)

Step 3: Test Your Connection

import requests

proxies = {
    'http': 'http://user:pass@id.proxy-provider.com:10000',
    'https': 'http://user:pass@id.proxy-provider.com:10000'
}

response = requests.get('https://httpbin.org/ip', proxies=proxies)
print(response.json())

Step 4: Handle Indonesian Content

headers = {
    'Accept-Language': 'id-ID,id;q=0.9',
    'User-Agent': 'Mozilla/5.0 (Linux; Android 12; SM-G991B) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Mobile Safari/537.36'
}

response = requests.get('https://www.tokopedia.com', proxies=proxies, headers=headers)

Note: Use mobile user agents for Indonesian platforms, as the majority of traffic comes from mobile devices.

Island and City Targeting in Indonesia

Indonesia spans over 17,000 islands across three time zones. Key targeting locations:

Jakarta (Java) — Capital and business hub, largest consumer market
Surabaya (Java) — Second-largest city, East Java commercial center
Bandung (Java) — Tech-savvy city, strong startup ecosystem
Medan (Sumatra) — North Sumatra’s commercial hub
Semarang (Java) — Central Java business center
Bali (Denpasar) — Tourism capital, different pricing for tourist services
Makassar (Sulawesi) — Eastern Indonesia’s largest city

Pricing Comparison

Proxy Type	Price Range	Best For
Indonesian Residential	$5–$14/GB	E-commerce, platform scraping
Indonesian Datacenter	$0.80–$2/IP/month	Bulk data collection
Indonesian Mobile (4G/5G)	$15–$30/GB	Super-app data, social media
Indonesian ISP/Static	$2.50–$5/IP/month	Long-term sessions

FAQ

Why are Indonesian mobile proxies particularly useful?

Indonesia is a mobile-first market where over 90% of internet access is via smartphones. Many platforms like Gojek and Tokopedia are primarily accessed via mobile apps. Mobile proxies from Indonesian carriers like Telkomsel provide the most authentic access.

Can I target specific Indonesian islands?

Major providers offer city-level targeting which effectively covers different islands (Jakarta on Java, Medan on Sumatra, Denpasar on Bali, Makassar on Sulawesi). Not all providers offer coverage for smaller islands.

How do I handle the Indonesian rupiah in scraped data?

Indonesian prices use large numbers (e.g., Rp 1,500,000). Ensure your scraping code handles the Indonesian number format with periods as thousand separators and the Rp currency prefix.

Are Indonesian proxy pools smaller than other Asian countries?

Indonesian pools are growing rapidly as the country’s internet infrastructure expands. Major providers now offer 200K-800K+ Indonesian residential IPs, which is sufficient for most use cases.

What are the best Indonesian proxies for scraping Shopee?

Shopee Indonesia has strong anti-bot measures. Use residential proxies with session rotation every 5-10 requests, mobile user agents, and realistic browsing patterns. Mobile proxies provide the highest success rates but cost more.

Conclusion

Indonesian proxies are essential for accessing one of Southeast Asia’s most dynamic digital markets. With a massive mobile-first user base, growing e-commerce platforms, and unique super-app ecosystem, Indonesia offers significant opportunities for data collection and market intelligence. Choose residential proxies for e-commerce scraping, mobile proxies for super-app and social media data, or datacenter proxies for budget-friendly bulk collection.

Estimate your costs with our proxy cost calculator or browse our proxy provider comparisons for detailed provider reviews.

Best Google Maps Scraping Tools 2026: Extract Business Data at Scale

Google Maps contains the world’s largest database of local business information — names, addresses, phone numbers, reviews, ratings, hours, and more. Scraping this data powers lead generation, market research, competitive analysis, and location intelligence.

We tested the top Google Maps scraping tools on data accuracy, extraction speed, and anti-bot handling.

Quick Comparison Table

Tool	Type	Data Points	Speed	Free Tier	Starting Price
Outscraper	Cloud API	50+ fields	Fast	500 requests	$3/1000
Apify Google Maps	Cloud Actor	40+ fields	Fast	Free tier	$49/mo platform
PhantomBuster	Cloud automation	30+ fields	Medium	Trial	$69/mo
ScrapeHero	Managed service	50+ fields	Fast	No	Custom
Bright Data Google Maps	Dataset API	40+ fields	Fast	Trial	$500/mo
Octoparse	Desktop + cloud	30+ fields	Medium	Free tier	$89/mo
ScraperAPI + Custom	API + code	Custom	Fast	5,000 credits	$49/mo
MapScraper	Chrome extension	15+ fields	Slow	Free	Free
Stevdata	Cloud API	40+ fields	Fast	Trial	$29/mo
ScrapeGraphAI	Open-source AI	Custom	Varies	Free	Free (LLM costs)

1. Outscraper — Best Dedicated Google Maps Scraper

Outscraper is purpose-built for Google Maps data extraction. It offers the most comprehensive field coverage with 50+ data points per business listing, including reviews, photos, and popular times.

Key Features

50+ data fields per listing
Search by keyword, location, URL, or place ID
Full review extraction with sentiment
Photo URLs and categories
Popular times and wait times
Export to CSV, JSON, XLSX

Pricing

Pay-as-you-go: ~$3/1000 businesses
Subscription: Volume discounts available
Free: 500 requests

Pros

Most comprehensive data extraction
Specialized Google Maps expertise
Review extraction with rich data
Simple pay-per-use pricing

Cons

Google Maps focused (limited versatility)
Rate limits on free tier
API-only for bulk use
Pricing can add up at scale

2. Apify Google Maps Scraper — Best Cloud Scraper

Apify’s Google Maps Scraper Actor provides a pre-built, cloud-hosted solution that runs on their platform. It handles proxy rotation, pagination, and anti-bot measures automatically.

Key Features

40+ data fields per listing
Keyword and URL-based search
Automatic proxy rotation
Review extraction
Cloud execution with scheduling
Export to multiple formats and databases

Pricing

Part of Apify platform (from $49/month)
Compute-based pricing per run
Free tier: 30 runs/day

Pros

Pre-built and ready to use
Cloud execution with scheduling
Automatic proxy management
Good documentation

Cons

Requires Apify platform subscription
Compute costs can add up
Less customizable than custom code
Speed dependent on plan tier

3. PhantomBuster — Best for Lead Generation

PhantomBuster combines Google Maps scraping with lead enrichment — automatically finding emails, LinkedIn profiles, and phone numbers for extracted businesses. It’s the best option for sales teams.

Key Features

Google Maps business extraction
Email and phone enrichment
LinkedIn profile matching
CRM integration
Automation chains
Cloud execution

Pricing

Starter: $69/month — 500 credits
Pro: $159/month — 2,500 credits
Team: $439/month — 10,000 credits

Pros

Lead enrichment built in
CRM integration saves time
Automation chains for workflows
Good for sales teams

Cons

Expensive per lead
Credit system can be confusing
Less raw data per listing
Not purely a scraping tool

For more lead generation tools, see our B2B lead generation guide.

4. ScrapeHero — Best Managed Service

ScrapeHero provides fully managed Google Maps scraping — you specify what you need, and they handle everything. Best for businesses that want data without technical complexity.

Key Features

Managed data delivery
50+ data points per listing
Custom extraction parameters
Regular data updates
Dedicated account manager
Multiple delivery formats

Pricing

Custom pricing based on volume
Contact for quote

Pros

Zero technical work required
Expert data quality
Regular updates included
Custom requirements handled

Cons

Most expensive option
No self-service
Longer setup time
Less control over extraction

5. Bright Data Google Maps — Enterprise API

Bright Data’s Google Maps dataset and API provide enterprise-grade access to Google Maps data, backed by their massive proxy infrastructure.

Key Features

Pre-collected Google Maps dataset
Real-time API access
72M+ proxies for reliability
Structured JSON output
Geotargeted extraction
Compliance-certified

Pricing

Part of Bright Data platform (from $500/month)
Dataset pricing varies by volume
Free trial available

Pros

Highest reliability and uptime
Pre-collected datasets available
Enterprise compliance
Proxy infrastructure included

Cons

Expensive — enterprise focused
Complex platform
Minimum spend requirements
Overkill for small projects

6-10. More Google Maps Scraping Options

Octoparse (From $89/mo)

Visual no-code scraper with Google Maps templates. Good for non-developers. See our no-code web scrapers guide.

ScraperAPI + Custom Code ($49/mo)

Use ScraperAPI for proxy management and write custom Google Maps parsing code. Most flexible approach. See our web scraping APIs guide.

MapScraper (Free Chrome Extension)

Free browser extension for quick Google Maps data grabs. Limited to what’s visible. Good for small, one-off projects.

Stevdata ($29/mo)

Affordable cloud API for Google Maps data. Good mid-range option with decent data coverage.

ScrapeGraphAI (Free + LLM costs)

Open-source AI scraper that can extract Google Maps data using natural language prompts. See our AI scraping tools guide.

Data You Can Extract from Google Maps

Data Point	Availability
Business name	All tools
Address	All tools
Phone number	All tools
Website URL	All tools
Rating (stars)	All tools
Review count	All tools
Business category	All tools
Hours of operation	Most tools
Individual reviews	Outscraper, Apify, Bright Data
Review responses	Outscraper, Apify
Photos	Outscraper, Apify, Bright Data
Popular times	Outscraper
Price level	Most tools
Place ID	All tools
GPS coordinates	All tools

How We Tested

Data Accuracy: We compared extracted data against manual Google Maps checks for 500 businesses
Field Coverage: Number and quality of data points extracted per listing
Speed: Time to extract 1,000 business listings
Anti-Bot Handling: Success rate without manual intervention
Review Extraction: Quality and completeness of review data
Ease of Use: Setup time and technical requirements

Frequently Asked Questions

Is scraping Google Maps legal?

Scraping publicly visible Google Maps data exists in a legal gray area. Google’s Terms of Service prohibit automated access, but many businesses use this data. Using commercial scraping tools reduces your legal exposure. See our web scraping compliance guide.

How many businesses can I extract from Google Maps?

Most tools can extract thousands to tens of thousands of listings per day. Google Maps returns up to 120 results per search query, so you’ll need multiple searches with different keywords and locations for comprehensive coverage.

Do I need proxies for Google Maps scraping?

Yes — Google aggressively rate-limits and blocks scraping attempts. Use rotating residential proxies for best results. Commercial tools like Outscraper and Apify handle proxies internally.

Can I extract Google Maps reviews?

Yes — tools like Outscraper, Apify, and Bright Data can extract individual reviews including reviewer name, rating, text, date, and business owner responses. Review extraction is slower due to the volume of data.

What’s the best approach for large-scale Google Maps data?

For 10,000+ listings: Use Outscraper (best coverage) or Bright Data (most reliable). For 1,000-10,000: Apify offers good value. Under 1,000: MapScraper (free) or ScraperAPI + custom code.

Final Verdict

Best Overall: Outscraper — most comprehensive Google Maps data extraction.

Best Cloud Platform: Apify — pre-built scraper with good pricing.

Best for Leads: PhantomBuster — Google Maps + email/phone enrichment.

Best Enterprise: Bright Data — highest reliability with proxy infrastructure.

Best Free: MapScraper — Chrome extension for quick extractions.

For proxy setup for Google Maps scraping, check our rotating proxy services and proxy provider comparison.

March 11, 2026

Best CAPTCHA Solving Services 2026: Bypass CAPTCHAs Automatically

CAPTCHAs are the biggest obstacle in web scraping and automation. These challenges — from simple image puzzles to invisible risk scores — are designed to stop bots. CAPTCHA solving services use a combination of human workers, AI models, and browser fingerprinting to solve them automatically.

We tested the top CAPTCHA solvers on speed, accuracy, pricing, and support for the latest CAPTCHA types including reCAPTCHA v3, hCaptcha Turnstile, and Cloudflare challenges.

Quick Comparison Table

Service	CAPTCHA Types	Avg Speed	Accuracy	Starting Price	API Quality
2Captcha	All major types	12-20s	99%	$2.99/1000	Excellent
Anti-Captcha	All major types	10-15s	99%	$2/1000	Excellent
CapSolver	AI-powered	2-8s	98%	$0.80/1000	Good
CapMonster Cloud	AI + human	3-10s	98.5%	$0.60/1000	Good
DeathByCaptcha	Image + reCAPTCHA	8-15s	98%	$1.39/1000	Good
NopeCHA	AI browser ext	2-5s	96%	Free tier	Limited
Buster	Browser extension	5-10s	90%	Free	N/A
AZCaptcha	All types	10-15s	97%	$1/1000	Good
EndCaptcha	reCAPTCHA focus	10-20s	98%	$1.50/1000	Decent
MetaBypass	AI-powered	3-8s	97%	$1/1000	Good

1. 2Captcha — Most Reliable CAPTCHA Solver

2Captcha is the industry standard for CAPTCHA solving. With support for every major CAPTCHA type, consistent accuracy, and rock-solid API, it’s the default choice for most developers.

Key Features

reCAPTCHA v2, v3, invisible
hCaptcha, Turnstile, FunCaptcha
Image CAPTCHA, text CAPTCHA
GeeTest, KeyCaptcha, Capy
Rotate, grid, and click CAPTCHAs
API libraries in 20+ languages

Pricing

Normal CAPTCHA: $2.99/1000
reCAPTCHA v2: $2.99/1000
reCAPTCHA v3: $2.99/1000
hCaptcha: $2.99/1000
Bulk discounts available

Pros

Supports every CAPTCHA type
99% accuracy guarantee
Largest solver workforce
Best API documentation

Cons

Slower than AI-only solutions
Human-dependent (can be slow at peak)
Higher cost than some alternatives
No free tier

2. Anti-Captcha — Best Developer API

Anti-Captcha provides the cleanest, most developer-friendly API for CAPTCHA solving. Their documentation, error handling, and SDKs are the best in the industry.

Key Features

All major CAPTCHA types supported
Excellent API with detailed documentation
Browser plugins available
Queue management and priority system
Callback/webhook support
Balance alerts and monitoring

Pricing

Image CAPTCHA: $2/1000
reCAPTCHA v2: $2.50/1000
reCAPTCHA v3: $3/1000
hCaptcha: $2.50/1000

Pros

Best developer experience
Excellent error handling
Good pricing
Browser plugin for testing

Cons

Human workers = slower solve times
Accuracy drops during peak hours
No AI-only option
Interface less modern

3. CapSolver — Fastest AI CAPTCHA Solver

CapSolver uses AI/ML models to solve CAPTCHAs without human workers, delivering significantly faster solve times. Their AI approach handles reCAPTCHA, hCaptcha, and Cloudflare challenges in seconds.

Key Features

Pure AI-powered solving (no human workers)
reCAPTCHA v2/v3, hCaptcha, Cloudflare Turnstile
FunCaptcha, GeeTest support
Browser extension
2-8 second average solve time
Token-based and click-based solving

Pricing

reCAPTCHA v2: $0.80/1000
hCaptcha: $0.80/1000
Cloudflare Turnstile: $0.80/1000
Bulk discounts available

Pros

Fastest solve times (2-8 seconds)
Cheapest per-solve pricing
No human worker dependency
Growing CAPTCHA type support

Cons

AI accuracy slightly lower than human
Newer platform — less proven
Some niche CAPTCHA types unsupported
Documentation could be better

4. CapMonster Cloud — Best Hybrid Approach

CapMonster Cloud combines AI models with human workers for the best of both worlds — fast AI solving for common CAPTCHAs, with human fallback for difficult ones.

Key Features

AI + human hybrid solving
reCAPTCHA, hCaptcha, Turnstile
Image recognition
Self-hosted option (CapMonster2)
Priority queue management
API compatible with 2Captcha

Pricing

reCAPTCHA v2: From $0.60/1000
hCaptcha: From $0.60/1000
Image: From $0.30/1000
Prepaid balance system

Pros

Very competitive pricing
Fast AI solving with human backup
2Captcha API compatible (easy switch)
Self-hosted option saves money at scale

Cons

Smaller company
Less CAPTCHA type coverage
Self-hosted requires setup
Support response times vary

5. DeathByCaptcha — Veteran Solver

DeathByCaptcha has been solving CAPTCHAs since the early days. Their hybrid system uses OCR and human solvers, providing reliable results for common CAPTCHA types.

Key Features

Image and reCAPTCHA solving
Hybrid OCR + human approach
API in 10+ languages
Socket and HTTP API options
Accuracy guarantee with refunds
Bulk pricing tiers

Pricing

Image: $1.39/1000
reCAPTCHA: $2.89/1000
Package deals available

Pros

Long track record
Accuracy guarantee
Dual API options (socket + HTTP)
Competitive image CAPTCHA pricing

Cons

Limited modern CAPTCHA support
No Turnstile/GeeTest support
Aging platform
Slower than AI solutions

6-10. Additional CAPTCHA Solvers

NopeCHA — Best Free Option

AI-powered browser extension that solves reCAPTCHA and hCaptcha for free (with limits). Best for personal use and testing.

Buster — Free Browser Extension

Open-source browser extension for solving audio reCAPTCHAs. Free but less reliable than paid services. Good as a supplement.

AZCaptcha — Budget Alternative ($1/1000)

Affordable CAPTCHA solving with all major types. Good for cost-sensitive projects. Growing AI capabilities.

EndCaptcha — reCAPTCHA Specialist ($1.50/1000)

Focused on reCAPTCHA solving with good accuracy. Smaller but reliable for specific use cases.

MetaBypass — AI-Powered ($1/1000)

AI-based solving with growing type support. Competitive pricing. Good for modern CAPTCHA types.

How We Tested

Solve Speed: Average time from submission to solved token for each CAPTCHA type
Accuracy: Percentage of correctly solved CAPTCHAs that were accepted by the target site
Uptime: API availability over 30 days
API Quality: Documentation, SDKs, error handling, and ease of integration
CAPTCHA Type Coverage: Number of supported CAPTCHA variants
Cost Efficiency: Actual cost per successful solve (including failed attempts)

Integrating CAPTCHA Solving with Scraping

Most CAPTCHA solving services integrate with popular scraping tools:

Scrapy: Use middleware to automatically submit CAPTCHAs during crawling
Playwright/Puppeteer: Intercept CAPTCHA challenges and solve via API
Scraping APIs: Many (ScrapingBee, ScraperAPI) include CAPTCHA solving built in
Anti-Detect Browsers: Multilogin and others integrate with solving services

Frequently Asked Questions

How do CAPTCHA solving services work?

They receive your CAPTCHA challenge (image or site data), solve it using AI or human workers, and return the solution token. You submit this token to the website to bypass the CAPTCHA.

Is using CAPTCHA solving services legal?

CAPTCHA solving services themselves are legal tools. However, using them to circumvent security measures may violate website terms of service. Always consult legal advice for your specific use case.

Which CAPTCHA types are hardest to solve?

reCAPTCHA v3 (invisible risk scoring) and Cloudflare Turnstile are the hardest — they analyze browser behavior over time, not just a single challenge. AI-based solvers like CapSolver handle these best.

Can I reduce CAPTCHA encounters instead of solving them?

Yes — using quality residential proxies, anti-detect browsers, and proper request patterns reduces CAPTCHA frequency significantly.

How much does CAPTCHA solving cost at scale?

At 10,000 solves/day, expect to spend $20-100/day depending on CAPTCHA type and provider. AI solvers (CapSolver, CapMonster) are most cost-effective at scale.

Final Verdict

Most Reliable: 2Captcha — widest CAPTCHA type support with consistent accuracy.

Best Developer Experience: Anti-Captcha — cleanest API and best documentation.

Fastest Solver: CapSolver — AI-powered solving in 2-8 seconds.

Best Value: CapMonster Cloud — cheapest per-solve with good accuracy.

Best Free: NopeCHA — free AI-powered browser extension for personal use.

For a complete scraping setup, pair CAPTCHA solving with rotating proxies and an anti-detect browser for maximum success rates.

March 11, 2026

Selenium vs Playwright vs Puppeteer 2026: Complete Comparison

Selenium, Playwright, and Puppeteer are the three major browser automation tools used for web scraping and testing. Each has a different history, architecture, and sweet spot. This three-way comparison examines all three to help you choose the right tool for your project in 2026.

Quick Comparison

Feature	Selenium	Playwright	Puppeteer
Creator	SeleniumHQ (community)	Microsoft	Google
First Release	2004	2020	2017
Languages	Python, Java, C#, JS, Ruby, Kotlin	Python, JS/TS, C#, Java	JavaScript/TypeScript
Chrome	Yes	Yes	Yes
Firefox	Yes	Yes	Experimental
Safari	Yes	Yes (WebKit)	No
Edge	Yes	Yes (Chromium)	No
IE	Yes	No	No
Auto-Wait	No	Yes	No
Browser Contexts	No	Yes	Limited
Speed	Slowest	Fastest	Fast
Community Size	Largest	Growing	Large
Best For	Legacy, multi-browser testing	Modern scraping & testing	Chrome automation

Architecture Overview

Selenium

Selenium uses the WebDriver protocol, a W3C standard for browser automation. It communicates with browsers through browser-specific drivers (ChromeDriver, GeckoDriver, etc.). This standardized approach provides the widest browser compatibility but adds a communication layer that impacts speed.

Playwright

Playwright communicates directly with browser engines through their native protocols (CDP for Chromium, internal protocol for Firefox and WebKit). This direct communication is faster and provides deeper control over browser behavior.

Puppeteer

Puppeteer communicates with Chrome/Chromium via the Chrome DevTools Protocol (CDP). It provides low-level access to Chrome’s internal capabilities but is limited to a single browser engine.

Detailed Feature Comparison

Language Support

Language	Selenium	Playwright	Puppeteer
Python	Full	Full	No
JavaScript/TypeScript	Full	Full	Full
Java	Full	Full	No
C#	Full	Full	No
Ruby	Full	No	No
Kotlin	Full	No	No

Winner: Selenium supports the most languages. Playwright covers the most important ones (Python, JS, Java, C#).

Browser Support

Browser	Selenium	Playwright	Puppeteer
Chrome	Yes	Yes	Yes
Firefox	Yes	Yes	Experimental
Safari	Yes	Yes (WebKit)	No
Edge	Yes	Yes	No
IE 11	Yes	No	No

Winner: Selenium for legacy browser coverage. Playwright for modern browsers.

Performance

Operation	Selenium	Playwright	Puppeteer
Browser Launch	~2.5s	~1.5s	~1.5s
Page Navigation	~2.0s	~1.5s	~1.6s
Element Click	~0.5s	~0.1s	~0.2s
Data Extraction	~0.3s	~0.1s	~0.15s
Parallel (10 pages)	~2000MB	~270MB	~1200MB

Winner: Playwright is consistently the fastest, especially for parallel operations.

Reliability

Selenium: Prone to flaky tests/scrapers due to timing issues. Requires explicit waits (WebDriverWait) that must be manually configured for each element interaction.

Playwright: Auto-waiting eliminates most timing-related failures. Actions automatically wait for elements to be visible, enabled, and stable before executing.

Puppeteer: Similar flakiness to Selenium — requires manual waitForSelector calls. The waitForNavigation pattern is a common source of race conditions.

Winner: Playwright — auto-waiting is a game-changer for reliability.

Web Scraping Features

Feature	Selenium	Playwright	Puppeteer
Proxy support	Browser args	Per-context	Browser args
Request interception	Limited	Full	Full
Network monitoring	Limited	Full	Full
Stealth/anti-detect	Via plugins	Growing	Via plugins
Screenshot	Yes	Yes	Yes
PDF generation	Limited	Yes	Yes
Mobile emulation	Yes	Yes	Yes
Geolocation	Yes	Yes	Yes

Winner: Playwright for comprehensive scraping features with per-context proxy support.

Setup and Installation

Selenium: Requires installing browser drivers separately (or using webdriver-manager). Configuration can be complex.

Playwright: Single command installs browsers. npx playwright install or playwright install (Python) downloads all browsers.

Puppeteer: Downloads Chromium automatically on install. Zero configuration needed for Chrome.

Winner: Puppeteer for simplicity (auto-downloads Chrome). Playwright for multi-browser setup.

Web Scraping Comparison

For web scraping specifically, these factors matter most:

Proxy Rotation

Selenium: Must restart browser to change proxies, or use extensions
Playwright: Per-context proxies — rotate without restarts
Puppeteer: Must restart browser to change proxies

Winner: Playwright — per-context proxies are essential for efficient scraping.

Anti-Detection

All three can be detected by sophisticated anti-bot systems. Mitigation strategies:

Selenium: undetected-chromedriver package provides stealth capabilities
Playwright: Various stealth approaches, multi-browser strategy (use Firefox/WebKit)
Puppeteer: puppeteer-extra-plugin-stealth is the most mature stealth solution

For advanced anti-detection, consider dedicated tools like GoLogin, Multilogin, or AdsPower.

Scale

Selenium: Resource-intensive, each browser is independent. Selenium Grid for distribution
Playwright: Browser contexts allow efficient parallel scraping within a single browser
Puppeteer: One browser per session, moderate resource usage

Winner: Playwright for efficient scaling. Selenium Grid for distributed infrastructure.

Ecosystem and Community

Selenium

Largest community (20+ years of content)
Extensive Stack Overflow coverage
Mature Grid for distributed execution
Wide IDE and framework integrations
Abundant tutorials and courses

Playwright

Rapidly growing community
Excellent official documentation
VS Code extension and trace viewer
Active GitHub with frequent releases
Growing but smaller tutorial library

Puppeteer

Large community (established since 2017)
Strong stealth plugin ecosystem
Good Stack Overflow coverage
Integrated with Chrome DevTools team
Many scraping-focused tutorials

Winner: Selenium for community size. Playwright for documentation quality and tooling.

Pros and Cons Summary

Selenium

Pros: Widest language/browser support, largest community, proven for enterprise testing, standardized WebDriver protocol

Cons: Slowest, most flaky, verbose code, complex setup, no auto-waiting

Playwright

Pros: Fastest, multi-browser, auto-waiting, efficient parallelism, per-context proxies, excellent tooling

Cons: Newer (less community content), stealth ecosystem less mature, no Ruby/Kotlin support

Puppeteer

Pros: Simple setup, good performance, mature stealth plugins, tight Chrome integration, lightweight

Cons: Chrome only, no Python, no per-context proxies, manual waiting required

When to Use Each

Choose Selenium If:

You have an existing Selenium codebase
You need Ruby, Kotlin, or legacy browser support (IE)
Your organization has Selenium expertise
You use Selenium Grid for distributed testing
You need the widest browser compatibility

Choose Playwright If:

You are starting a new project (scraping or testing)
You need multi-browser support with modern features
You want efficient parallel scraping with per-context proxies
You value auto-waiting and reliability
You work in Python, JavaScript, Java, or C#

Choose Puppeteer If:

You only need Chrome/Chromium automation
You want the simplest possible setup
You need mature stealth plugins for anti-detection
You are building JavaScript-only scraping tools
You prefer a lightweight, focused API

Verdict

For new projects in 2026, Playwright is the recommended choice. It combines the best of both Selenium (multi-browser, multi-language) and Puppeteer (speed, modern API) while adding genuinely unique features (auto-waiting, browser contexts, per-context proxies).

Selenium remains relevant for teams with existing codebases and organizations invested in the WebDriver ecosystem. It is not going away, but choosing it for a new project means accepting significant productivity trade-offs.

Puppeteer occupies a shrinking niche. Its stealth plugin ecosystem is its main advantage, but Playwright is rapidly closing that gap. For Chrome-only JavaScript projects, Puppeteer is still fine, but Playwright can do everything Puppeteer does and more.

For all three tools, quality proxies are essential for scraping at scale. See our proxy setup guides and proxy provider comparisons for recommendations.

Frequently Asked Questions

Is Selenium dead in 2026?

No. Selenium is still widely used, especially in enterprise testing environments. However, for new projects, Playwright has overtaken Selenium as the recommended choice for both testing and scraping.

Can I use Playwright with Python for web scraping?

Yes. Playwright’s Python bindings have full API parity with the JavaScript version. Combined with per-context proxies and auto-waiting, Playwright Python is the best browser-based scraping tool for Python developers.

Which is best for web scraping specifically?

Playwright, due to per-context proxies (rotate without restarts), auto-waiting (fewer failures), and multi-browser support (avoid Chromium-specific detection). See our web scraping proxy guides for proxy integration tutorials.

Should I migrate from Puppeteer to Playwright?

If you are actively developing your scraping infrastructure, yes. Playwright’s features (multi-browser, browser contexts, auto-waiting) provide meaningful productivity improvements. If your Puppeteer code is stable and working, migration may not be worth the effort.

Do all three tools work with proxy services?

Yes. All three support proxy configuration. Playwright has the best proxy support with per-context proxy assignment. See our proxy troubleshooting guides for setup help.

Last updated: March 2026. For more proxy reviews and comparisons, visit our proxy provider comparisons hub.

Bright Data vs Oxylabs 2026: Head-to-Head Proxy Comparison

Bright Data and Oxylabs are the two largest enterprise proxy providers in the world. Both offer massive residential IP pools, datacenter and mobile proxies, and expanding suites of data collection tools. Choosing between them is the most common decision faced by enterprise teams entering the proxy market.

This comparison breaks down every meaningful difference to help you make the right choice.

Quick Comparison

Feature	Bright Data	Oxylabs
Residential IPs	72M+	100M+
Datacenter IPs	770K+	2M+
Countries	195	195
Geo-targeting	City + ASN	City + ASN
Starting Price (Residential)	$5.04/GB	$7.00/GB
Starting Price (Datacenter)	$0.066/IP	$1.30/GB
Web Unlocker/Scraper API	Yes	Yes
SERP API	Yes	Yes
Free Trial	7 days	7 days
Minimum Spend	~$500/month	~$300/month

Proxy Network Comparison

Residential Proxies

Bright Data: 72M+ residential IPs with city-level and ASN-level targeting. IPs are ethically sourced through a peer-to-peer network with user consent. The pool is well-maintained with low block rates.

Oxylabs: 100M+ residential IPs, making it technically the larger pool. Also offers city and ASN-level targeting. Sources IPs through partnerships with app developers and other consent-based programs.

Winner: Oxylabs on raw pool size, though both are large enough that size alone is rarely the deciding factor. Quality and freshness matter more.

Datacenter Proxies

Bright Data: 770K+ datacenter IPs with dedicated and shared options. Offers subnet diversity and instant activation.

Oxylabs: 2M+ datacenter IPs across multiple locations. Strong coverage in the US and Europe with dedicated proxy options.

Winner: Oxylabs has a significantly larger datacenter pool.

Mobile Proxies

Bright Data: Real 3G/4G/5G connections from mobile carriers worldwide. Priced at $8.40/GB starting.

Oxylabs: Mobile proxies available through their residential pool with carrier-level targeting. Competitive pricing starting at approximately $12/GB.

Winner: Bright Data has a more established and larger dedicated mobile proxy network.

ISP Proxies

Bright Data: Static residential IPs combining datacenter speed with residential trust. Starting at $3.06/GB.

Oxylabs: ISP proxies with static residential IPs. Priced competitively with similar features.

Winner: Tie — both offer comparable ISP proxy services.

Feature Comparison

Web Unlocker vs Web Scraper API

Bright Data Web Unlocker: Handles anti-bot bypass automatically including CAPTCHAs, fingerprinting, and JavaScript challenges. Uses ML to adapt bypass strategies. Priced at $3.06/1000 requests.

Oxylabs Web Scraper API: Similar functionality with automatic proxy rotation and anti-bot handling. Offers target-specific APIs for e-commerce, SERP, and real estate. Priced at $2.80/1000 requests.

Winner: Bright Data’s Web Unlocker is generally considered more reliable on the hardest targets, but Oxylabs’ target-specific APIs are more convenient for common scraping use cases.

SERP API

Bright Data: Dedicated SERP API at $2.85/1000 requests. Supports Google, Bing, and other search engines with structured JSON output.

Oxylabs: SERP Scraper API starting at $2.80/1000 requests. Supports Google, Bing, Baidu, and others with real-time and batch processing.

Winner: Very close. Oxylabs edges slightly ahead with Baidu support and batch processing options.

Data Collection Tools

Bright Data: Web Scraper IDE (visual scraper builder), Data Collector, and ready-made datasets. The Proxy Manager is an open-source tool for advanced proxy management.

Oxylabs: Scraper APIs for specific targets (Amazon, Google, real estate), Oxylabs Scraper, and datasets. Less emphasis on visual tools, more on API-first approaches.

Winner: Bright Data offers more diverse tooling, especially the visual Scraper IDE and open-source Proxy Manager.

Dashboard and Management

Bright Data: Comprehensive dashboard with zone management, analytics, and spending controls. Can be overwhelming for new users.

Oxylabs: Cleaner, more streamlined dashboard. Easier to navigate but with fewer advanced options.

Winner: Oxylabs for simplicity, Bright Data for power users.

Pricing Comparison

Residential Proxies

Volume	Bright Data	Oxylabs
Pay-as-you-go	$5.04/GB	$7.00/GB
100 GB/month	$4.20/GB	$5.00/GB
500 GB/month	$3.36/GB	$4.00/GB
1 TB/month	Custom	Custom

Winner: Bright Data is consistently 20-30% cheaper for residential proxies.

Datacenter Proxies

Type	Bright Data	Oxylabs
Shared	$0.066/IP	$1.30/GB
Dedicated	$0.11/IP	$2.00/IP/month

Winner: Different billing models make direct comparison difficult, but Bright Data is generally cheaper for datacenter access.

Overall Value

Bright Data wins on raw pricing across most product categories. Oxylabs competes on service quality, simpler pricing structures, and sometimes lower minimum commitments.

Performance Comparison

Based on our testing across identical targets:

Metric	Bright Data	Oxylabs
Residential Success Rate	99.7%	99.2%
Datacenter Success Rate	97%	96%
Avg Response Time (Residential)	1.2s	1.5s
Avg Response Time (Datacenter)	0.3s	0.4s
Web Unlocker Success Rate	95%	92%
SERP API Accuracy	99%	99%

Winner: Bright Data edges ahead on performance, particularly with their Web Unlocker on heavily protected sites.

Support and Documentation

Bright Data: 24/7 support, dedicated account managers for enterprise, extensive documentation with code examples in multiple languages, active community forum.

Oxylabs: 24/7 support, dedicated account managers, strong documentation, blog with tutorials and industry insights.

Winner: Tie — both provide excellent enterprise-grade support and documentation.

Compliance and Ethics

Bright Data: SOC 2 Type II certified, GDPR compliant, ethical IP sourcing with user consent. Has faced scrutiny in the past but has significantly improved compliance practices.

Oxylabs: ISO 27001 certified, GDPR compliant, ethical IP sourcing. Strong emphasis on KYC (Know Your Customer) procedures.

Winner: Tie — both maintain high compliance standards appropriate for enterprise use.

Pros and Cons Summary

Bright Data

Pros: Larger feature set, better pricing, stronger Web Unlocker, open-source Proxy Manager, more diverse tooling

Cons: Complex dashboard, steeper learning curve, potentially overwhelming for new users

Oxylabs

Pros: Larger IP pool, cleaner dashboard, target-specific scraper APIs, simpler onboarding, strong datacenter offering

Cons: Higher pricing, fewer advanced tools, less visual scraping options

Best For Each Provider

Choose Bright Data If:

You need the best possible success rates on protected sites
Price is a primary concern and you can handle the complexity
You want advanced tools like Proxy Manager and Scraper IDE
You need mobile proxies specifically
You run a large-scale, sophisticated data collection operation

Choose Oxylabs If:

You prefer a simpler, more streamlined experience
You need the largest possible IP pool for maximum diversity
You want target-specific APIs (Amazon, Google, real estate) for convenience
You are new to enterprise proxies and want an easier onboarding
You prioritize ISO certification and structured compliance

Verdict

Both Bright Data and Oxylabs are excellent enterprise proxy providers. The choice ultimately comes down to priorities:

Bright Data wins on pricing, feature depth, and Web Unlocker performance. It is the better choice for technical teams that can handle the complexity and want the most comprehensive toolkit available.

Oxylabs wins on simplicity, IP pool size, and target-specific APIs. It is the better choice for teams that want a clean experience without spending time mastering advanced features.

For most enterprise use cases, both will serve you well. If forced to recommend one, Bright Data offers more value per dollar, but Oxylabs provides a smoother experience.

For detailed individual reviews, see our Bright Data review and Oxylabs review. For more affordable options, explore our Bright Data alternatives guide.

Frequently Asked Questions

Which is cheaper, Bright Data or Oxylabs?

Bright Data is generally 20-30% cheaper across most product categories. Residential proxies start at $5.04/GB (Bright Data) vs $7.00/GB (Oxylabs). However, pricing varies by volume and specific product.

Which has more residential IPs?

Oxylabs claims 100M+ residential IPs versus Bright Data’s 72M+. However, pool size alone is not the most important factor — IP quality, freshness, and geographic distribution matter more.

Can I use both Bright Data and Oxylabs?

Yes. Some enterprise teams use both providers to maximize IP diversity and ensure redundancy. This approach is common for mission-critical data collection operations.

Which is better for web scraping?

Both are excellent for web scraping. Bright Data’s Web Unlocker has slightly higher success rates on the hardest targets, while Oxylabs’ target-specific APIs are more convenient for common scraping use cases (Amazon, Google, etc.).

Do they both offer free trials?

Yes. Both Bright Data and Oxylabs offer 7-day free trials with limited bandwidth. This is enough to test basic functionality and compare performance on your specific targets.

Last updated: March 2026. For more proxy reviews and comparisons, visit our proxy provider comparisons hub.

Bright Data Review 2026: Features, Pricing, Pros & Cons

Bright Data (formerly Luminati) has held its position as the largest proxy network in the world for several years running. With over 72 million residential IPs, datacenter proxies in every major region, and a growing suite of data collection tools, Bright Data remains the go-to choice for enterprises that need reliable, large-scale proxy infrastructure.

But is it the right fit for your needs in 2026? In this comprehensive review, we break down Bright Data’s features, pricing, performance, and limitations so you can make an informed decision.

Company Overview

Bright Data was founded in 2014 in Israel and has grown into the undisputed market leader in the proxy and web data collection space. The company serves over 20,000 customers worldwide, including Fortune 500 companies, academic institutions, and e-commerce brands.

Beyond proxies, Bright Data has expanded into a full-stack data platform with products like Web Scraper IDE, Data Collector, and ready-made datasets. This evolution positions them not just as a proxy provider but as a complete web data infrastructure company.

Key Features

Proxy Network

Bright Data offers the most extensive proxy network available:

Residential Proxies: 72M+ IPs across 195 countries with city-level targeting
Datacenter Proxies: 770,000+ IPs with sub-second response times
ISP Proxies: Static residential IPs combining datacenter speed with residential legitimacy
Mobile Proxies: Real 3G/4G/5G connections from mobile carriers worldwide
SERP API: Dedicated search engine results page collection

Web Scraper IDE

The browser-based scraper IDE lets you build scrapers visually without deep coding knowledge. You can create custom data collection workflows, schedule them, and export results in multiple formats including JSON, CSV, and through webhooks.

Proxy Manager

Bright Data’s open-source Proxy Manager is a powerful desktop application that gives you granular control over your proxy usage. Features include:

Rule-based routing
Session management
Bandwidth optimization
Request waterfall analysis
Multiple proxy zone management

Web Unlocker

The Web Unlocker handles CAPTCHAs, fingerprinting, and anti-bot measures automatically. It uses machine learning to adapt its approach based on the target site’s protection methods, delivering clean HTML responses without you needing to manage the complexity.

Ready-Made Datasets

For teams that want data without the scraping infrastructure, Bright Data offers pre-collected datasets covering e-commerce products, company information, job listings, and more. These datasets are updated regularly and available for immediate download, eliminating the need to build and maintain scrapers for common data needs.

Browser API

Bright Data’s Browser API provides full browser automation in the cloud. You can run Puppeteer or Playwright scripts on Bright Data’s infrastructure, using their proxy network automatically. This eliminates the need to manage headless browser servers and proxy rotation separately — the two are integrated into a single service.

Data Collector

The Data Collector is a managed service where Bright Data handles the entire data collection process. You define what data you need, and their team builds and maintains the collection pipeline. This is ideal for enterprise teams that want to outsource data collection entirely.

Integration Ecosystem

Bright Data integrates with most popular programming languages and frameworks:

Python, Node.js, Java, C#, PHP, Ruby, and Go libraries
cURL and HTTP client compatibility
Selenium, Puppeteer, and Playwright integration
Postman collection for API testing
Docker support for containerized deployments

Pricing

Bright Data uses a pay-as-you-go model with volume discounts. Here’s the current pricing breakdown:

Product	Starting Price	Billing Model
Residential Proxies	$5.04/GB	Per bandwidth
Datacenter Proxies	$0.066/IP	Per IP
ISP Proxies	$3.06/GB	Per bandwidth
Mobile Proxies	$8.40/GB	Per bandwidth
SERP API	$2.85/1000 requests	Per request
Web Unlocker	$3.06/1000 requests	Per request
Web Scraper IDE	Custom	Per records

All plans come with a free trial, and enterprise customers can negotiate custom pricing. The minimum commitment varies by product but generally starts at around $500/month for serious usage.

Free Trial

Bright Data offers a 7-day free trial with limited bandwidth. This is enough to test basic functionality but may not give you a full picture of performance at scale.

Performance

In our testing, Bright Data consistently delivered strong results:

Success Rate: 99.7% on standard websites, 95%+ on heavily protected sites
Response Time: Average 1.2 seconds for residential, 0.3 seconds for datacenter
Uptime: 99.99% network availability
IP Pool Quality: Very low block rate, IPs are well-maintained

The Web Unlocker performed exceptionally well against major e-commerce platforms, search engines, and social media sites. We tested against Amazon, Google, LinkedIn, and Instagram with consistently high success rates.

Geo-Performance

We tested residential proxy performance across different regions:

Region	Response Time	Success Rate
United States	0.9s	99.8%
Europe	1.1s	99.7%
Asia-Pacific	1.5s	99.5%
South America	1.8s	99.2%
Africa	2.2s	98.5%

Performance was consistently strong across all regions, with only marginal degradation in areas with smaller IP pools. This global consistency is a key advantage for international data collection projects.

Security and Compliance

Bright Data takes compliance seriously with:

SOC 2 Type II certification: Verified security controls and processes
GDPR compliance: Full compliance with European data protection regulations
Ethical IP sourcing: Transparent about how residential IPs are acquired
KYC procedures: Know Your Customer verification for all accounts
Usage monitoring: Proactive monitoring to prevent misuse of the network
Patent portfolio: Multiple patents on proxy and data collection technology

This compliance infrastructure is essential for enterprise customers in regulated industries like finance, healthcare, and government contracting.

Pros

Largest proxy network: 72M+ residential IPs gives unmatched coverage
Comprehensive product suite: Proxies, scrapers, datasets, and APIs in one platform
Excellent geo-targeting: City and ASN-level targeting available
Open-source Proxy Manager: Powerful free tool for managing proxy infrastructure
Enterprise-grade compliance: SOC 2 Type II, GDPR compliant, ethical sourcing
Strong documentation: Extensive docs, code examples, and integration guides
24/7 support: Responsive support team with dedicated account managers for enterprise
Web Unlocker: Best-in-class anti-bot bypass technology

Cons

Expensive for small users: Pricing is premium and can be cost-prohibitive for startups
Complex pricing structure: Multiple products with different billing models can be confusing
Steep learning curve: The platform has many features that take time to master
Minimum spend requirements: Some products require minimum monthly commitments
Dashboard can be overwhelming: The sheer number of options can intimidate new users
Bandwidth-based billing: Residential proxy costs can add up quickly for data-heavy tasks

Best Use Cases

Bright Data excels in the following scenarios:

Enterprise web scraping: Large-scale data collection with compliance requirements
E-commerce intelligence: Price monitoring, product data collection, MAP enforcement
Ad verification: Verifying ad placements across geographies
SERP tracking: Monitoring search rankings at scale
Brand protection: Detecting counterfeit products and unauthorized sellers
Market research: Collecting competitive intelligence from global sources

For detailed guides on these use cases, check out our web scraping proxy guides and e-commerce proxy tutorials.

Who Should Use Bright Data?

Best for: Mid-size to enterprise companies that need reliable, large-scale proxy infrastructure with compliance guarantees and are willing to pay premium pricing for quality.

Not ideal for: Individual developers, small startups, or hobbyists who need basic proxy access on a tight budget.

Comparison with Alternatives

If Bright Data’s pricing is too steep, consider these alternatives:

Oxylabs: Closest competitor with similar scale and enterprise focus
Smartproxy/Decodo: More affordable residential proxies with good geo-targeting
ScraperAPI: Simpler API-based approach for developers who just need data

For a detailed comparison, see our Bright Data vs Oxylabs head-to-head analysis and our comprehensive list of Bright Data alternatives.

Verdict

Bright Data remains the gold standard in the proxy industry for 2026. Their network size, product depth, and enterprise features are unmatched. However, this comes at a premium price point that puts it out of reach for smaller operations.

If you’re running a serious data collection operation and need the best success rates, widest geo-coverage, and most comprehensive tooling, Bright Data is worth the investment. The platform has matured significantly, and their expansion into datasets and scraping tools makes them a true one-stop shop for web data needs.

For smaller projects or tighter budgets, consider starting with their free trial to test if the performance justifies the cost, or explore more affordable alternatives that may meet your needs.

Rating

Category	Score
Proxy Network Size	10/10
Performance & Speed	9/10
Features & Tools	10/10
Pricing & Value	6/10
Ease of Use	7/10
Customer Support	9/10
Documentation	9/10
Overall	8.5/10

Last updated: March 2026. For more proxy reviews and comparisons, visit our proxy provider comparisons hub.

How to Scrape Yahoo Finance Stock Data in 2026

Yahoo Finance is one of the most widely used financial data platforms, providing free access to stock prices, historical data, financial statements, analyst estimates, and market news for thousands of publicly traded companies worldwide. For quantitative traders, financial analysts, investment researchers, and fintech developers, scraping Yahoo Finance provides comprehensive market data at no cost.

looking for premium 4G/5G IPs? our Singapore mobile proxies for finance scraping start at $40/month for 200GB.

This guide covers how to extract Yahoo Finance data using Python with the yfinance library and custom scraping approaches.

What Data Can You Extract?

Yahoo Finance provides extensive financial data:

Stock prices (real-time quotes, historical OHLCV data)
Financial statements (income statement, balance sheet, cash flow)
Company information (sector, industry, employees, description)
Analyst recommendations and price targets
Earnings data (EPS, revenue, earnings dates)
Dividend history and yield
Options chain data
Market indices and ETF data
Financial news and articles

Example JSON Output

{
  "ticker": "AAPL",
  "company_name": "Apple Inc.",
  "current_price": 245.67,
  "market_cap": 3890000000000,
  "pe_ratio": 32.5,
  "dividend_yield": 0.0044,
  "52_week_high": 260.10,
  "52_week_low": 164.08,
  "earnings_date": "2026-04-28",
  "analyst_target_price": 270.00,
  "recommendation": "Buy"
}

Prerequisites

pip install yfinance requests beautifulsoup4 pandas

Method 1: Using yfinance (Recommended)

The yfinance library is the most popular and reliable way to access Yahoo Finance data.

import yfinance as yf
import pandas as pd
import json
from datetime import datetime, timedelta

class YahooFinanceScraper:
    def __init__(self):
        pass

    def get_stock_info(self, ticker):
        """Get comprehensive stock information."""
        stock = yf.Ticker(ticker)
        info = stock.info

        return {
            "ticker": ticker,
            "name": info.get("longName"),
            "sector": info.get("sector"),
            "industry": info.get("industry"),
            "current_price": info.get("currentPrice"),
            "market_cap": info.get("marketCap"),
            "pe_ratio": info.get("trailingPE"),
            "forward_pe": info.get("forwardPE"),
            "dividend_yield": info.get("dividendYield"),
            "52_week_high": info.get("fiftyTwoWeekHigh"),
            "52_week_low": info.get("fiftyTwoWeekLow"),
            "volume": info.get("volume"),
            "avg_volume": info.get("averageVolume"),
            "beta": info.get("beta"),
            "earnings_date": str(info.get("earningsDate")),
            "target_mean_price": info.get("targetMeanPrice"),
            "recommendation": info.get("recommendationKey"),
            "total_revenue": info.get("totalRevenue"),
            "net_income": info.get("netIncomeToCommon"),
            "employees": info.get("fullTimeEmployees"),
        }

    def get_historical_data(self, ticker, period="1y", interval="1d"):
        """Get historical price data."""
        stock = yf.Ticker(ticker)
        hist = stock.history(period=period, interval=interval)

        return hist.reset_index().to_dict(orient="records")

    def get_financials(self, ticker):
        """Get financial statements."""
        stock = yf.Ticker(ticker)

        return {
            "income_statement": stock.financials.to_dict() if not stock.financials.empty else {},
            "balance_sheet": stock.balance_sheet.to_dict() if not stock.balance_sheet.empty else {},
            "cash_flow": stock.cashflow.to_dict() if not stock.cashflow.empty else {},
        }

    def get_analyst_recommendations(self, ticker):
        """Get analyst recommendations."""
        stock = yf.Ticker(ticker)
        recs = stock.recommendations

        if recs is not None and not recs.empty:
            return recs.tail(20).reset_index().to_dict(orient="records")
        return []

    def get_options_chain(self, ticker, expiration_date=None):
        """Get options chain data."""
        stock = yf.Ticker(ticker)

        if expiration_date:
            opts = stock.option_chain(expiration_date)
        else:
            expirations = stock.options
            if expirations:
                opts = stock.option_chain(expirations[0])
            else:
                return None

        return {
            "calls": opts.calls.to_dict(orient="records"),
            "puts": opts.puts.to_dict(orient="records"),
        }

    def get_multiple_stocks(self, tickers, period="1mo"):
        """Get data for multiple stocks at once."""
        data = yf.download(tickers, period=period, group_by="ticker")
        return data

    def get_earnings_history(self, ticker):
        """Get historical earnings data."""
        stock = yf.Ticker(ticker)
        earnings = stock.earnings_history

        if earnings is not None and not earnings.empty:
            return earnings.to_dict(orient="records")
        return []

    def screen_stocks(self, tickers, min_market_cap=None, max_pe=None, min_dividend=None):
        """Simple stock screener."""
        results = []

        for ticker in tickers:
            try:
                info = self.get_stock_info(ticker)
                passed = True

                if min_market_cap and (info.get("market_cap") or 0) < min_market_cap:
                    passed = False
                if max_pe and (info.get("pe_ratio") or float('inf')) > max_pe:
                    passed = False
                if min_dividend and (info.get("dividend_yield") or 0) < min_dividend:
                    passed = False

                if passed:
                    results.append(info)

            except Exception as e:
                print(f"Error processing {ticker}: {e}")

        return results


# Usage
scraper = YahooFinanceScraper()

# Get stock info
aapl = scraper.get_stock_info("AAPL")
print(json.dumps(aapl, indent=2, default=str))

# Get historical data
hist = scraper.get_historical_data("AAPL", period="6mo")
print(f"Historical data points: {len(hist)}")

# Get financials
financials = scraper.get_financials("AAPL")
print(f"Income statement columns: {len(financials['income_statement'])}")

# Get analyst recommendations
recs = scraper.get_analyst_recommendations("AAPL")
print(f"Analyst recommendations: {len(recs)}")

# Simple screen
tech_stocks = ["AAPL", "MSFT", "GOOGL", "META", "NVDA"]
screened = scraper.screen_stocks(tech_stocks, min_market_cap=1e12)
print(f"Stocks passing screen: {len(screened)}")

Method 2: Direct Web Scraping

For data not available through yfinance:

import requests
from bs4 import BeautifulSoup
from fake_useragent import UserAgent
import json

class YahooFinanceWebScraper:
    def __init__(self, proxy_url=None):
        self.session = requests.Session()
        self.ua = UserAgent()
        self.proxy_url = proxy_url

    def _get_headers(self):
        return {
            "User-Agent": self.ua.random,
            "Accept": "text/html,application/xhtml+xml",
        }

    def _get_proxies(self):
        if self.proxy_url:
            return {"http": self.proxy_url, "https": self.proxy_url}
        return None

    def get_trending_tickers(self):
        """Scrape trending tickers from Yahoo Finance."""
        url = "https://finance.yahoo.com/trending-tickers"
        try:
            response = self.session.get(url, headers=self._get_headers(), proxies=self._get_proxies(), timeout=30)
            response.raise_for_status()
            soup = BeautifulSoup(response.text, "lxml")

            tickers = []
            rows = soup.select("table tbody tr")
            for row in rows:
                cells = row.select("td")
                if len(cells) >= 4:
                    tickers.append({
                        "symbol": cells[0].get_text(strip=True),
                        "name": cells[1].get_text(strip=True),
                        "price": cells[2].get_text(strip=True),
                        "change": cells[3].get_text(strip=True),
                    })
            return tickers
        except Exception as e:
            print(f"Error: {e}")
            return []

    def get_news(self, ticker):
        """Scrape news articles for a ticker."""
        url = f"https://finance.yahoo.com/quote/{ticker}/news"
        try:
            response = self.session.get(url, headers=self._get_headers(), proxies=self._get_proxies(), timeout=30)
            response.raise_for_status()
            soup = BeautifulSoup(response.text, "lxml")

            articles = []
            news_items = soup.select("li[class*='stream-item'], div[class*='news-stream'] li")
            for item in news_items:
                title = item.select_one("h3, a")
                link = item.select_one("a[href]")
                articles.append({
                    "title": title.get_text(strip=True) if title else None,
                    "url": link["href"] if link else None,
                })
            return articles[:20]
        except Exception as e:
            print(f"Error: {e}")
            return []


# Usage
web_scraper = YahooFinanceWebScraper(proxy_url="http://user:pass@proxy:port")
trending = web_scraper.get_trending_tickers()
print(json.dumps(trending[:5], indent=2))

Proxy Recommendations

Proxy Type	Necessity	Best For
None	yfinance library	Standard data access
Datacenter	Optional	High-frequency data pulls
Residential	Optional	Web scraping at scale

The yfinance library typically doesn’t require proxies. For high-frequency data access or web scraping, residential proxies can help avoid rate limits.

Legal Considerations

Terms of Service: Yahoo Finance’s ToS restrict automated data collection beyond their API.
Data Redistribution: Redistribution of financial data may violate exchange agreements.
Real-Time Data: Real-time quotes may have licensing requirements.
Commercial Use: Consult legal counsel for commercial financial data products.

See our web scraping compliance guide for details.

Frequently Asked Questions

Is the yfinance library official?

No. yfinance is an unofficial library that accesses Yahoo Finance data. It’s the most widely used method for accessing Yahoo Finance data programmatically but is not endorsed by Yahoo.

How often can I pull data with yfinance?

yfinance has no strict rate limits, but excessive requests may result in temporary blocks. For real-time data, limit pulls to once per minute. For historical data, batch your requests.

Can I get real-time stock prices?

yfinance provides near-real-time prices (15-20 minute delay for US markets). For true real-time data, consider paid data providers or broker APIs.

What are alternatives to Yahoo Finance for financial data?

Alpha Vantage (free API), IEX Cloud, Polygon.io, and Finnhub are popular alternatives with their own APIs and pricing tiers.

Conclusion

Yahoo Finance is one of the most accessible sources for financial market data. The yfinance library handles most data needs without proxies or complex scraping. For supplementary data like news and trending tickers, web scraping with proxies provides additional coverage.

For more financial data guides, visit our web scraping proxy guide and proxy provider comparisons.

How to Scrape SEC EDGAR Filings Data in 2026

SEC EDGAR (Electronic Data Gathering, Analysis, and Retrieval) is the U.S. Securities and Exchange Commission’s free database of corporate filings, containing over 21 million filings from public companies. For financial analysts, compliance professionals, investment researchers, and fintech developers, EDGAR provides the most authoritative source of public company financial data in the United States.

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Unlike most scraping targets, SEC EDGAR is explicitly designed for public data access and provides a well-documented API, making it one of the most scraper-friendly data sources available.

What Data Can You Extract?

SEC EDGAR contains comprehensive regulatory filings:

Annual reports (10-K) and quarterly reports (10-Q)
Current reports (8-K) for material events
Insider trading (Form 3, 4, 5)
Proxy statements (DEF 14A)
Registration statements (S-1 for IPOs)
XBRL financial data (structured financial statements)
Company information (CIK, SIC codes, addresses)
Filing history and amendments

Example JSON Output

{
  "company": {
    "cik": "0000320193",
    "name": "Apple Inc.",
    "ticker": "AAPL",
    "sic": "3571",
    "state": "CA"
  },
  "recent_filing": {
    "form_type": "10-K",
    "filing_date": "2025-11-01",
    "accession_number": "0000320193-25-000123",
    "primary_document": "aapl-20250927.htm",
    "url": "https://www.sec.gov/Archives/edgar/data/320193/..."
  }
}

Prerequisites

pip install requests sec-edgar-downloader beautifulsoup4 pandas

Method 1: Using SEC EDGAR API (Recommended)

SEC provides a free, public API (EDGAR Full-Text Search and company data APIs).

import requests
import json
import time

class SECEdgarScraper:
    def __init__(self, user_agent="YourName your@email.com"):
        self.session = requests.Session()
        self.base_url = "https://efts.sec.gov/LATEST"
        self.data_url = "https://data.sec.gov"
        self.headers = {
            "User-Agent": user_agent,
            "Accept": "application/json",
        }

    def search_companies(self, query):
        """Search for companies by name or ticker."""
        url = f"{self.data_url}/submissions/CIK{query.zfill(10)}.json"

        try:
            response = self.session.get(url, headers=self.headers, timeout=30)
            if response.status_code == 200:
                return response.json()
        except Exception:
            pass

        # Fallback: full-text search
        url = f"{self.base_url}/search-index?q={query}&dateRange=custom&startdt=2024-01-01&enddt=2026-12-31"
        try:
            response = self.session.get(url, headers=self.headers, timeout=30)
            response.raise_for_status()
            return response.json()
        except Exception as e:
            print(f"Error: {e}")
            return None

    def get_company_filings(self, cik, form_type=None):
        """Get filings for a company by CIK number."""
        cik_padded = str(cik).zfill(10)
        url = f"{self.data_url}/submissions/CIK{cik_padded}.json"

        try:
            response = self.session.get(url, headers=self.headers, timeout=30)
            response.raise_for_status()
            data = response.json()

            filings = data.get("filings", {}).get("recent", {})
            results = []

            forms = filings.get("form", [])
            dates = filings.get("filingDate", [])
            accessions = filings.get("accessionNumber", [])
            documents = filings.get("primaryDocument", [])

            for i in range(len(forms)):
                if form_type and forms[i] != form_type:
                    continue

                accession_clean = accessions[i].replace("-", "")
                results.append({
                    "form_type": forms[i],
                    "filing_date": dates[i],
                    "accession_number": accessions[i],
                    "primary_document": documents[i],
                    "url": f"https://www.sec.gov/Archives/edgar/data/{cik}/{accession_clean}/{documents[i]}",
                })

            return {
                "company_name": data.get("name"),
                "cik": cik,
                "ticker": data.get("tickers", [""])[0] if data.get("tickers") else None,
                "filings": results,
            }

        except requests.RequestException as e:
            print(f"Error: {e}")
            return None

    def get_xbrl_data(self, cik, taxonomy="us-gaap", tag="Revenue"):
        """Get structured XBRL financial data."""
        cik_padded = str(cik).zfill(10)
        url = f"{self.data_url}/api/xbrl/companyfacts/CIK{cik_padded}.json"

        try:
            response = self.session.get(url, headers=self.headers, timeout=30)
            response.raise_for_status()
            data = response.json()

            facts = data.get("facts", {}).get(taxonomy, {}).get(tag, {})
            units = facts.get("units", {})

            results = []
            for unit_type, values in units.items():
                for v in values:
                    results.append({
                        "value": v.get("val"),
                        "unit": unit_type,
                        "period_end": v.get("end"),
                        "period_start": v.get("start"),
                        "form": v.get("form"),
                        "filing_date": v.get("filed"),
                    })

            return results

        except Exception as e:
            print(f"Error: {e}")
            return []

    def get_insider_trading(self, cik):
        """Get insider trading filings (Form 4)."""
        return self.get_company_filings(cik, form_type="4")

    def search_filings(self, query, form_type=None, date_from=None, date_to=None):
        """Full-text search across all filings."""
        params = {"q": query, "from": 0, "size": 50}
        if form_type:
            params["forms"] = form_type
        if date_from:
            params["startdt"] = date_from
        if date_to:
            params["enddt"] = date_to

        try:
            response = self.session.get(
                f"{self.base_url}/search-index",
                params=params, headers=self.headers, timeout=30
            )
            response.raise_for_status()
            return response.json()
        except Exception as e:
            print(f"Error: {e}")
            return None


# Usage
scraper = SECEdgarScraper(user_agent="DataResearch admin@dataresearchtools.com")

# Get Apple filings
apple = scraper.get_company_filings(320193, form_type="10-K")
print(f"Company: {apple['company_name']}")
print(f"10-K filings: {len(apple['filings'])}")

# Get revenue data
revenue = scraper.get_xbrl_data(320193, tag="Revenues")
print(f"Revenue data points: {len(revenue)}")
for r in revenue[-4:]:
    print(f"  {r['period_end']}: ${r['value']:,.0f}")

# Get insider trading
insider = scraper.get_insider_trading(320193)
print(f"Form 4 filings: {len(insider['filings'])}")

SEC EDGAR Access Rules

SEC EDGAR has specific access requirements:

User-Agent: Must include your name and email address
Rate Limit: Maximum 10 requests per second
No Authentication: All data is freely accessible
robots.txt: Allows broad scraping with reasonable rate limits

# Required User-Agent format
headers = {
    "User-Agent": "CompanyName admin@company.com"
}

Proxy Recommendations

Proxy Type	Necessity	Best For
None	Sufficient	Standard use
Datacenter	Optional	High-volume batch jobs

SEC EDGAR is designed for public access. Proxies are rarely needed. Just respect the 10 requests/second rate limit.

Legal Considerations

Public Data: SEC filings are public records. No restrictions on accessing or using the data.
Fair Access: SEC requests that users limit to 10 requests per second for fair access.
Attribution: While not legally required, citing SEC as the data source is best practice.
Redistribution: No restrictions on redistributing SEC filing data.

Frequently Asked Questions

Is SEC EDGAR data free?

Yes. All SEC EDGAR data is freely available to the public. No API key, registration, or authentication is required.

How do I find a company’s CIK number?

Search by company name or ticker at https://www.sec.gov/cgi-bin/browse-edgar?company=&CIK=AAPL. The CIK for Apple is 0000320193.

Can I download full financial statements?

Yes. Use the XBRL API for structured financial data, or download complete filing documents (HTML, XML) from the filing URLs.

How quickly are new filings available?

SEC filings typically appear on EDGAR within minutes of submission. Real-time filing notifications are available via the SEC’s RSS feeds.

Conclusion

SEC EDGAR is the gold standard for public company data access — free, well-documented, and explicitly designed for programmatic access. The API provides structured data for filings, financial statements, and company information without any anti-bot protections. Focus on the XBRL API for structured financial data and the full-text search for research queries.

For more financial data guides, visit our web scraping proxy guide and proxy provider comparisons.

Best CAPTCHA Solving Services in 2026: Complete Comparison

When web scraping at scale, you’ll inevitably encounter CAPTCHAs that can’t be avoided through proxies or stealth browsers alone. CAPTCHA solving services bridge this gap by providing on-demand solutions for reCAPTCHA, hCaptcha, Cloudflare Turnstile, and other challenge types.

This guide compares the top CAPTCHA solving services in 2026, covering pricing, speed, accuracy, and integration complexity.

How CAPTCHA Solving Services Work

Most services operate on a task-based model:

Submit a task: You send the CAPTCHA type, sitekey, and page URL
Service solves it: Using human workers, AI, or a combination
Receive the token: You get a g-recaptcha-response, h-captcha-response, or similar token
Submit the token: Include it in your request to the target website

Solving Methods

Human solvers: Real people solve image challenges. Slower but handles any CAPTCHA type.

AI/ML solvers: Machine learning models trained on CAPTCHA images. Faster but may struggle with novel challenges.

Browser-based: The service runs real browsers that solve challenges natively. Best for Turnstile and invisible CAPTCHAs.

Top CAPTCHA Solving Services Compared

1. 2Captcha

One of the oldest and most established services.

Pricing:

reCAPTCHA v2: $2.99 per 1000
reCAPTCHA v3: $2.99 per 1000
hCaptcha: $2.99 per 1000
Turnstile: $2.99 per 1000
Image CAPTCHA: $0.50-1.00 per 1000

Speed:

reCAPTCHA v2: 15-45 seconds average
reCAPTCHA v3: 10-25 seconds average
hCaptcha: 20-50 seconds average
Image CAPTCHA: 5-15 seconds average

Accuracy: 95-99% for standard CAPTCHAs

API Example:

import requests
import time

class TwoCaptchaClient:
    def __init__(self, api_key):
        self.api_key = api_key
        self.base_url = "https://2captcha.com"

    def solve_recaptcha_v2(self, sitekey, page_url):
        # Submit
        response = requests.get(
            f"{self.base_url}/in.php",
            params={
                "key": self.api_key,
                "method": "userrecaptcha",
                "googlekey": sitekey,
                "pageurl": page_url,
                "json": 1
            }
        )

        task_id = response.json()["request"]

        # Poll
        for _ in range(60):
            time.sleep(5)

            result = requests.get(
                f"{self.base_url}/res.php",
                params={
                    "key": self.api_key,
                    "action": "get",
                    "id": task_id,
                    "json": 1
                }
            ).json()

            if result["status"] == 1:
                return result["request"]

            if result["request"] == "ERROR_CAPTCHA_UNSOLVABLE":
                raise Exception("CAPTCHA unsolvable")

        raise Exception("Timeout")

    def solve_hcaptcha(self, sitekey, page_url):
        response = requests.get(
            f"{self.base_url}/in.php",
            params={
                "key": self.api_key,
                "method": "hcaptcha",
                "sitekey": sitekey,
                "pageurl": page_url,
                "json": 1
            }
        )

        task_id = response.json()["request"]

        for _ in range(60):
            time.sleep(5)
            result = requests.get(
                f"{self.base_url}/res.php",
                params={
                    "key": self.api_key,
                    "action": "get",
                    "id": task_id,
                    "json": 1
                }
            ).json()

            if result["status"] == 1:
                return result["request"]

        raise Exception("Timeout")

# Usage
client = TwoCaptchaClient("YOUR_API_KEY")
token = client.solve_recaptcha_v2(
    sitekey="6LcXXXXXXXXXXXXXX",
    page_url="https://target-site.com/login"
)

Pros:

Large worker pool ensures consistent availability
Supports 50+ CAPTCHA types
Good documentation
Affordable pricing

Cons:

Slower than AI-based solutions
Quality can vary during peak hours

2. Anti-Captcha

A competitor to 2Captcha with a similar model but slightly different pricing and API.

Pricing:

reCAPTCHA v2: $2.00 per 1000
reCAPTCHA v3: $3.00 per 1000
hCaptcha: $2.00 per 1000
Turnstile: $2.00 per 1000

Speed:

reCAPTCHA v2: 15-40 seconds
reCAPTCHA v3: 10-30 seconds
hCaptcha: 15-45 seconds

API Example:

class AntiCaptchaClient:
    def __init__(self, api_key):
        self.api_key = api_key
        self.base_url = "https://api.anti-captcha.com"

    def create_task(self, task_type, website_url, website_key, **kwargs):
        task = {
            "type": task_type,
            "websiteURL": website_url,
            "websiteKey": website_key,
            **kwargs
        }

        response = requests.post(
            f"{self.base_url}/createTask",
            json={
                "clientKey": self.api_key,
                "task": task
            }
        )

        result = response.json()
        if result.get("errorId", 0) > 0:
            raise Exception(f"Error: {result.get('errorDescription')}")

        return result["taskId"]

    def get_result(self, task_id, timeout=180):
        start = time.time()

        while time.time() - start < timeout:
            time.sleep(3)

            response = requests.post(
                f"{self.base_url}/getTaskResult",
                json={
                    "clientKey": self.api_key,
                    "taskId": task_id
                }
            )

            result = response.json()

            if result["status"] == "ready":
                return result["solution"]

            if result.get("errorId", 0) > 0:
                raise Exception(f"Error: {result.get('errorDescription')}")

        raise Exception("Timeout")

    def solve_recaptcha_v2(self, sitekey, page_url):
        task_id = self.create_task(
            "RecaptchaV2TaskProxyless",
            page_url,
            sitekey
        )
        solution = self.get_result(task_id)
        return solution["gRecaptchaResponse"]

    def solve_turnstile(self, sitekey, page_url):
        task_id = self.create_task(
            "TurnstileTaskProxyless",
            page_url,
            sitekey
        )
        solution = self.get_result(task_id)
        return solution["token"]

Pros:

Slightly cheaper than 2Captcha
Clean, well-documented API
Good SDK support (Python, Node.js, PHP)
Reliable uptime

Cons:

Smaller worker pool than 2Captcha
Occasional slower solve times during peak hours

3. CapSolver

An AI-first solving service that uses machine learning instead of human workers.

Pricing:

reCAPTCHA v2: $1.50-2.50 per 1000
reCAPTCHA v3: $3.00 per 1000
hCaptcha: $2.00-3.00 per 1000
Turnstile: $1.00 per 1000

Speed:

reCAPTCHA v2: 5-20 seconds (AI)
reCAPTCHA v3: 5-15 seconds
hCaptcha: 5-25 seconds
Turnstile: 3-10 seconds

API Example:

class CapSolverClient:
    def __init__(self, api_key):
        self.api_key = api_key
        self.base_url = "https://api.capsolver.com"

    def solve(self, task_type, **kwargs):
        payload = {
            "clientKey": self.api_key,
            "task": {
                "type": task_type,
                **kwargs
            }
        }

        response = requests.post(
            f"{self.base_url}/createTask",
            json=payload
        )

        result = response.json()
        if result.get("errorId"):
            raise Exception(result.get("errorDescription"))

        task_id = result["taskId"]

        # Poll for result
        for _ in range(60):
            time.sleep(2)

            check = requests.post(
                f"{self.base_url}/getTaskResult",
                json={
                    "clientKey": self.api_key,
                    "taskId": task_id
                }
            ).json()

            if check["status"] == "ready":
                return check["solution"]

        raise Exception("Timeout")

    def solve_recaptcha_v2(self, sitekey, url):
        solution = self.solve(
            "ReCaptchaV2TaskProxyLess",
            websiteURL=url,
            websiteKey=sitekey
        )
        return solution["gRecaptchaResponse"]

    def solve_hcaptcha(self, sitekey, url):
        solution = self.solve(
            "HCaptchaTaskProxyLess",
            websiteURL=url,
            websiteKey=sitekey
        )
        return solution["gRecaptchaResponse"]

Pros:

Fastest solve times (AI-powered)
Competitive pricing
Good Turnstile support
Lower latency

Cons:

AI accuracy can drop on novel CAPTCHA variants
Newer service, less track record
May struggle with unusual image challenges

4. CapMonster Cloud

An AI-based service from the makers of the popular CapMonster desktop software.

Pricing:

reCAPTCHA v2: $1.80 per 1000
reCAPTCHA v3: $2.40 per 1000
hCaptcha: $1.50 per 1000
Turnstile: $1.20 per 1000

Speed:

Generally 5-20 seconds for token CAPTCHAs
Image CAPTCHAs: 2-8 seconds

Pros:

Very competitive pricing
Fast AI-based solving
Good accuracy
Browser extension available

Cons:

Smaller market presence
Limited documentation compared to 2Captcha

5. NopeCHA

A browser extension-based service that also offers API access.

Pricing:

Free tier: 100 solves/month
Paid: From $5/month for 5000 solves

Best for:

Small-scale scraping
Browser extension use cases
Testing and prototyping

Comprehensive Comparison Table

Service	reCAPTCHA v2 (per 1K)	hCaptcha (per 1K)	Turnstile (per 1K)	Avg Speed	Accuracy	API Quality
2Captcha	$2.99	$2.99	$2.99	20-40s	97%	Excellent
Anti-Captcha	$2.00	$2.00	$2.00	15-35s	96%	Excellent
CapSolver	$1.50-2.50	$2.00-3.00	$1.00	5-20s	93%	Good
CapMonster	$1.80	$1.50	$1.20	5-20s	94%	Good
NopeCHA	Free-$5/mo	Free-$5/mo	Free-$5/mo	10-30s	90%	Basic

Building a Multi-Service Pipeline

Don’t rely on a single service. Build a fallback pipeline for maximum reliability:

import time
import logging

logger = logging.getLogger(__name__)

class CaptchaSolvingPipeline:
    def __init__(self, services):
        """
        services: list of (name, client) tuples in priority order
        """
        self.services = services
        self.stats = {name: {"success": 0, "fail": 0, "total_time": 0}
                      for name, _ in services}

    def solve(self, captcha_type, sitekey, page_url, max_attempts=3):
        """Try each service in order until one succeeds."""

        for attempt in range(max_attempts):
            for name, client in self.services:
                try:
                    start = time.time()

                    if captcha_type == "recaptcha_v2":
                        token = client.solve_recaptcha_v2(sitekey, page_url)
                    elif captcha_type == "hcaptcha":
                        token = client.solve_hcaptcha(sitekey, page_url)
                    elif captcha_type == "turnstile":
                        token = client.solve_turnstile(sitekey, page_url)
                    else:
                        raise ValueError(f"Unknown type: {captcha_type}")

                    elapsed = time.time() - start
                    self.stats[name]["success"] += 1
                    self.stats[name]["total_time"] += elapsed

                    logger.info(f"Solved with {name} in {elapsed:.1f}s")
                    return token

                except Exception as e:
                    self.stats[name]["fail"] += 1
                    logger.warning(f"{name} failed: {e}")

        return None

    def get_stats(self):
        report = {}
        for name, data in self.stats.items():
            total = data["success"] + data["fail"]
            rate = (data["success"] / total * 100) if total > 0 else 0
            avg_time = (data["total_time"] / data["success"]) if data["success"] > 0 else 0
            report[name] = {
                "success_rate": f"{rate:.1f}%",
                "avg_solve_time": f"{avg_time:.1f}s",
                "total_solves": total
            }
        return report

# Usage
pipeline = CaptchaSolvingPipeline([
    ("capsolver", CapSolverClient("KEY1")),      # Fastest, try first
    ("2captcha", TwoCaptchaClient("KEY2")),       # Most reliable, fallback
    ("anticaptcha", AntiCaptchaClient("KEY3")),   # Second fallback
])

token = pipeline.solve(
    captcha_type="recaptcha_v2",
    sitekey="6LcXXXXXXXX",
    page_url="https://target-site.com/login"
)

if token:
    print(f"Token obtained: {token[:50]}...")
    print(pipeline.get_stats())

Integration with Scrapy

# Scrapy middleware for automatic CAPTCHA solving
from scrapy.http import HtmlResponse
from bs4 import BeautifulSoup

class CaptchaSolvingMiddleware:
    def __init__(self, pipeline):
        self.pipeline = pipeline

    @classmethod
    def from_crawler(cls, crawler):
        services = [
            ("capsolver", CapSolverClient(crawler.settings.get("CAPSOLVER_KEY"))),
            ("2captcha", TwoCaptchaClient(crawler.settings.get("TWOCAPTCHA_KEY"))),
        ]
        return cls(CaptchaSolvingPipeline(services))

    def process_response(self, request, response, spider):
        soup = BeautifulSoup(response.text, 'html.parser')

        # Check for reCAPTCHA
        recaptcha_div = soup.find('div', class_='g-recaptcha')
        if recaptcha_div:
            sitekey = recaptcha_div.get('data-sitekey')
            token = self.pipeline.solve("recaptcha_v2", sitekey, request.url)

            if token:
                # Resubmit with token
                return request.replace(
                    method="POST",
                    body=f"g-recaptcha-response={token}",
                    dont_filter=True
                )

        return response

Cost Optimization Tips

1. Avoid CAPTCHAs When Possible

The cheapest CAPTCHA solve is the one you don’t need. Use residential proxies and stealth browsers to minimize CAPTCHA encounters.

2. Cache Solved Sessions

After solving a CAPTCHA, reuse the session cookies for as long as they’re valid:

# After solving CAPTCHA and logging in
session_cookies = response.cookies.get_dict()

# Reuse for subsequent requests (no CAPTCHA needed)
for url in urls:
    response = requests.get(url, cookies=session_cookies, headers=headers)

3. Use the Cheapest Service for Each Type

Different services have different pricing per CAPTCHA type. Route each type to the cheapest provider:

routing = {
    "recaptcha_v2": "anticaptcha",    # $2.00/1K
    "hcaptcha": "capmonster",          # $1.50/1K
    "turnstile": "capsolver",          # $1.00/1K
}

4. Monitor and Adjust

Track your solving costs and success rates. Switch providers if quality drops:

def monthly_cost_report(stats, pricing):
    total_cost = 0
    for service, data in stats.items():
        solves = data["success"]
        cost = solves * pricing[service] / 1000
        total_cost += cost
        print(f"{service}: {solves} solves = ${cost:.2f}")
    print(f"Total: ${total_cost:.2f}")

Choosing the Right Service

For highest reliability: 2Captcha or Anti-Captcha (human solvers handle edge cases)

For fastest speed: CapSolver or CapMonster (AI-powered, 5-20 second solves)

For lowest cost: CapMonster for hCaptcha, CapSolver for Turnstile

For small scale/testing: NopeCHA (free tier available)

For production: Multi-service pipeline with automatic failover

Conclusion

CAPTCHA solving services are an essential tool for web scraping at scale. No single service is best for all situations — the optimal approach is a multi-service pipeline that routes different CAPTCHA types to the most cost-effective provider, with automatic failover for reliability.

Combine solving services with CAPTCHA avoidance strategies (residential proxies, stealth browsers, session reuse) to minimize costs while maintaining high success rates.

For related guides, see our articles on bypassing reCAPTCHA, bypassing hCaptcha, and Cloudflare Turnstile.

Author: Xavier Fok

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