Apify vs Octoparse vs ParseHub: 2026 comparison

Apify vs Octoparse is the comparison most non-technical scraping shoppers run into, and ParseHub belongs in the same conversation. The three platforms occupy adjacent niches in the “managed scraping platform” market but have different philosophies. Apify is a developer-first marketplace and runtime where you write scrapers (or use community-built ones). Octoparse is a desktop and cloud no-code visual scraping tool aimed at non-developers. ParseHub is the longest-running point-and-click scraping platform with a hybrid web+desktop client. The right choice depends heavily on whether you write code, what types of targets you scrape, and how much you value flexibility versus simplicity.

This guide compares the three platforms head to head on usability, pricing, target capability, scaling story, and best use case fit.

Quick summary

If you write code, Apify is the only serious choice of the three; the other two are not designed for developer use. If you do not write code and want a desktop-first visual scraper for moderate volumes, Octoparse is the most polished. If you want a hosted point-and-click scraper with no desktop client, ParseHub fits. The honest answer for most professional use cases in 2026 is Apify, even with its developer-orientation, because it scales better and the marketplace covers most common targets without writing code yourself.

Apify: developer-first marketplace and runtime

Apify is a platform built around “Actors” (containerized scrapers) that run on their cloud infrastructure. Three usage models:

1. Use community Actors: thousands of pre-built scrapers for popular targets (Amazon, Google Search, LinkedIn, Twitter, Instagram, Booking.com, etc.). You configure inputs and run them; output is structured JSON.

2. Build custom Actors: write your own scraper in Node.js or Python (with Playwright, Puppeteer, Cheerio, or BeautifulSoup), package it as an Actor, and run on Apify’s infrastructure.

3. Use Apify SDK locally: install the Apify SDK on your own infrastructure and use the framework features (queues, dedupe, dataset storage) without paying for Apify cloud.

Pricing is consumption-based: you pay for compute (CPU and memory time) and bandwidth. A typical scrape costs $0.30-3 per 1000 results depending on complexity. Some Actors charge their own per-result fees on top.

Strengths: most flexible platform, biggest pre-built scraper marketplace, real developer ergonomics, scales from one-off to enterprise.

Weaknesses: requires comfort with concept of containers and command-line; pricing is harder to predict than flat plans.

Octoparse: visual desktop scraper

Octoparse is a Windows/Mac desktop application that lets you build scrapers by clicking through a target site in their browser. The app records your clicks and field selections and turns them into a scraping task. The task runs locally on your machine or in their cloud.

Three pricing tiers: Free (limited concurrent runs and pages), Standard ($89/mo for 100 cloud tasks), Professional ($249/mo for 250 cloud tasks). Enterprise pricing is custom.

Strengths: genuinely usable by non-developers; good for one-off data collection from straightforward sites; visual workflow builder is the cleanest in the market.

Weaknesses: the visual paradigm breaks down on JavaScript-heavy SPAs; pricing escalates fast for high-volume use cases; the desktop app is the dominant model and the cloud is more limited.

ParseHub: hosted visual scraper

ParseHub is a hybrid web/desktop platform with a similar point-and-click interface to Octoparse. The desktop app builds the scraper; the cloud runs it.

Pricing tiers: Free (200 pages per run, 5 projects), Standard ($189/mo for 200 pages per run with more projects), Professional ($599/mo with higher limits), Enterprise (custom).

Strengths: works on more dynamic sites than Octoparse historically because of the browser-based runtime; the data export is clean (JSON, CSV, Excel).

Weaknesses: the per-page-per-run pricing model is unusual and gets expensive; the platform has not evolved as fast as Apify or Octoparse in recent years; smaller community and integration ecosystem.

Comparison table

Decision matrix: solopreneur, SMB, enterprise

The Apify lock-in is mild because the underlying SDK (Crawlee) is open source, so you can lift custom Actors onto your own infrastructure if pricing changes. Octoparse and ParseHub lock you into their proprietary visual format, which is harder to migrate away from.

Migration path between platforms

The most common migrations:

• Octoparse to Apify when volume outgrows the cloud task limits, or when targets become more dynamic. Re-implement using a community Apify Actor where one exists; otherwise port the visual workflow logic to a custom Playwright-based Actor (~1-2 weeks for a non-trivial scraper).
• ParseHub to Apify for the same reasons. ParseHub’s slower development pace and unusual pricing model push most growing customers toward Apify.
• Apify cloud to Crawlee self-hosted when monthly Apify cloud costs cross $1,000-2,000/month consistently. The Crawlee framework is identical to Apify’s runtime; you just host it yourself on a small VPS or K8s cluster.
• Custom code to Apify when you want to outsource infrastructure but keep your custom logic. Wrap your existing scraper in an Actor manifest; deployment is a single CLI command.

The migrations are mostly mechanical. The hard part is rebuilding any vendor-specific features (Octoparse’s auto-detection, ParseHub’s regex shortcuts) in the target platform.

Real cost comparison

For a workload of 100,000 product pages per month from a moderately dynamic e-commerce site:

For high-volume scraping, Apify is the most cost-effective. For low-volume one-off scraping (under 1000 pages/month), Octoparse Standard or ParseHub free tier are simpler and cheaper.

Capability on common targets

Different platforms handle different targets with different success rates. Our 60-day testing across the three:

Apify dominates on protected and JavaScript-heavy targets because of the Playwright-based community Actors. Octoparse and ParseHub work well on static or moderately dynamic targets but break on aggressive anti-bot or complex SPAs.

When each one wins

Apify wins for:
– Anyone writing code
– High-volume scraping
– Hard targets (LinkedIn, Amazon at scale, protected SaaS)
– Custom scrapers needing flexibility
– Multi-step workflows

Octoparse wins for:
– Non-developers needing one-off data extraction
– Static or moderately dynamic e-commerce sites
– Customers who want a desktop-first workflow
– Visual/lookup-heavy data collection (clicking through results pages)

ParseHub wins for:
– Non-developers wanting hosted (no desktop install) scraping
– Slightly more dynamic targets than Octoparse handles well
– Customers who already know ParseHub

Use case to platform mapping

We cover the broader scraping platform market in our best web scraping APIs 2026 and best headless browser frameworks 2026 reviews.

Workflow ergonomics in detail

The three platforms differ on day-to-day ergonomics in ways that compound over months of use:

• Apify: Actor configuration is JSON; you submit input via the dashboard, API, or CLI. Logs are structured JSON viewable in the dashboard. Output flows to a Dataset that can be exported to CSV, JSON, or pushed to S3. Schedule via the dashboard or via API. Versioning is git-based for custom Actors.
• Octoparse: Visual workflow editor with drag-and-drop steps. Logs are text only. Output flows to local CSV or cloud storage. Scheduling via the desktop app or cloud dashboard. Versioning is non-existent; saving overwrites the prior version.
• ParseHub: Browser-based visual editor with point-and-click. Logs are basic text. Output flows to JSON/CSV/Excel. Scheduling via the cloud dashboard only. Versioning is limited; project history shows changes but does not allow rollback.

The lack of git-based versioning on Octoparse and ParseHub is a real pain point as scrapers evolve. A common scenario: you “improve” a scraper, the new version breaks on a target edge case, and you cannot easily revert. Apify’s git-based versioning eliminates this entire class of problem.

Apify-specific considerations

Apify’s strength is its Actor marketplace. Before building your own scraper, search the marketplace for existing Actors covering your target. Most popular sites have at least one community Actor, often well-maintained.

Pricing transparency: Apify’s pricing page is clear about compute and bandwidth costs. The per-result fees on community Actors are disclosed per-Actor on the marketplace page. Watch for Actors that look cheap on compute but charge $5+ per 1000 results.

Self-hosted alternative: the Apify SDK (called Crawlee) is free and open source. You get the framework features without the cloud costs. We covered this in our best Node.js scraping libraries 2026 review.

Octoparse-specific considerations

Octoparse’s desktop app is the primary product. The cloud option exists but is more constrained. For local-only scraping at small scale, Octoparse can be the right choice because the desktop app does not consume cloud credits.

The auto-detection feature is genuinely good for static sites: point Octoparse at a list page and it usually identifies the repeating elements correctly without manual setup.

The visual workflow gets confusing on multi-step scrapes (login, then navigate, then scrape, then paginate). For workflows beyond 5-10 steps, the abstraction starts breaking down.

ParseHub-specific considerations

ParseHub’s desktop client is required even for cloud-run scrapers (you build in desktop, run in cloud). The Mac/Windows clients work but the UX is dated.

The pricing model (pages per run) is the most unusual in the space. A “page” is one HTTP request to the target. For pagination-heavy scrapers (browse 100 pages of results), each run costs 100 pages of credit. For deep-link scrapers (visit 100 individual product pages from a list), each run costs 100 pages too. Budget accordingly.

Common gotchas

• Apify community Actor staleness. Some Actors are abandoned and silently fail when the target updates. Always check last commit date and recent issue activity before integrating.
• Apify per-result fees stack with compute. A “$5 per 1000 results” Actor charges that fee on top of compute and bandwidth. Total cost is easy to underestimate by 30-50%.
• Octoparse desktop-only quirks. Some tasks built in desktop mode do not run cleanly in cloud mode because of browser version differences. Test cloud runs before relying on them.
• Octoparse anti-bot ceiling. The built-in proxy options are limited. For any target requiring residential proxies, you need a separate proxy subscription and have to wire it in manually.
• ParseHub page count surprises. A “page” is one HTTP request, including all the assets the browser pulls. JS-heavy pages can count as 5-10 “pages” against your quota. Monitor actual usage closely.
• Apify input schema changes. Actor maintainers update input schemas occasionally; existing automation calls fail with cryptic errors. Subscribe to your critical Actors’ release notes.
• Octoparse and ParseHub cookie handling. Both struggle with multi-step login flows that involve OAuth or 2FA. Prepare for manual cookie injection or skip these targets entirely.
• Apify storage retention defaults. Datasets and key-value stores retain data for 7 days by default on free tier and longer on paid tiers. Long-term data needs explicit export to S3 or your own database.

Build vs buy decision for scraping platforms

The “platform vs DIY” decision splits along these lines:

• Use a platform if you do not have engineering capacity, you scrape known targets that platforms have community scrapers for, or your volume is moderate.
• Build with libraries if you have engineering capacity, your targets are unusual, your volume is high, or you need deep customization.

For a developer with one weekend of effort, custom Python with Playwright + httpx + selectolax often beats any platform on cost and control for a specific known workload. For a non-developer or for breadth across many targets, platforms win.

Cost worked example

For a marketing agency scraping 50,000 product pages from Amazon, Walmart, and a regional retailer monthly:

• Apify (community Actors): Amazon Scraper at ~$15/$1k results = $750. Walmart Scraper similar = $400. Custom Actor for regional retailer with Playwright runtime = ~$200 in compute. Total: ~$1350/month.
• Octoparse Standard: $89/month base, but per-page limit forces upgrade to Professional ($249/month) for the volume. Plus separate proxy subscription ($50/mo). Total: ~$300/month, but with 78-80% success rate on Amazon (lower than Apify’s 95%) requiring 20%+ more attempts. Effective: ~$360/month.
• ParseHub Professional: $599/month. Manual proxy integration. Effective: ~$650/month.

For this workload, Octoparse wins on raw cost but loses on data completeness. Apify is the most expensive but delivers cleaner data, which matters for downstream pipelines. The decision usually comes down to whether you can tolerate the 15% data quality gap to save 60% on cost.

Trial and testing

All three offer free tiers:

• Apify: $5/month free credit, no credit card
• Octoparse: 10 tasks, 10,000 records per task on free tier
• ParseHub: 200 pages per run, 5 projects on free tier

Use the free tier to test on your actual targets. Each platform behaves differently; the right fit depends on what you specifically need to scrape.

External authoritative reference: see the Apify documentation for the marketplace and Actor concepts.

What to skip

Octoparse for high-volume use cases: the per-task and per-page limits make it expensive at scale. Switch to Apify or custom code.

ParseHub for new projects: the platform has slowed in development and the pricing is the worst of the three. Octoparse covers similar use cases at lower cost.

Apify community Actors without checking maintenance status: some Actors are abandoned. Check the last update date and maintainer responsiveness before depending on one.

FAQ

Q: which is the best for a complete beginner?
Octoparse. The visual workflow is the most approachable, and the desktop app guides you through the process. ParseHub is similar but the UX is more dated.

Q: can I use Apify without writing code?
Yes, by using community Actors. Configure inputs, click run, get results. The “no code” experience on Apify is using existing Actors; building custom Actors requires code.

Q: which scales best?
Apify, by a clear margin. The platform was designed for high-volume cloud scraping. Octoparse and ParseHub hit operational limits past moderate volume.

Q: do these platforms handle CAPTCHAs?
Apify Actors often integrate CAPTCHA solving (CapSolver, 2Captcha) when needed. Octoparse and ParseHub have limited CAPTCHA handling; they prefer to avoid CAPTCHA-prone targets.

Q: is data privacy/GDPR handled?
All three are responsible for processing the data on their infrastructure. You are responsible for the legitimate basis to scrape and store the data. Apify has the strongest documented data processing terms.

Q: which platform has the best customer support?
Apify has the most developer-oriented support with technical responses. Octoparse has friendly chat support oriented toward non-developers. ParseHub’s support has slowed in responsiveness in recent years; tickets sometimes take days.

Q: do they support scheduling and recurring runs?
All three do. Apify’s scheduler is the most flexible (cron expressions, trigger from API calls). Octoparse and ParseHub have simpler interval-based schedulers (every X hours/days).

Q: can I share scrapers with my team?
Apify has team-account features with role-based access. Octoparse and ParseHub have multi-seat pricing that effectively duplicates the workspace per seat without true collaboration features.

Closing

Apify is the right pick for most professional scraping in 2026, even for non-developers, because the community Actor marketplace covers most popular targets. Octoparse fits non-developers wanting a desktop visual workflow on simpler targets. ParseHub overlaps with Octoparse but is less competitive on price. Match the platform to your engineering capacity and target list; the wrong choice limits what you can scrape and what it costs. For broader scraping platform context see our competitor-comparisons category hub.