Apify vs Bright Data vs Oxylabs: Managed Scraping Platforms Compared (2026)

apify is the developer-friendly platform with a marketplace of 3000+ pre-built scrapers (called actors). bright data has the deepest catalog of pre-scraped datasets and the most complete proxy + unlocker infrastructure. oxylabs is the enterprise-grade api stack with the cleanest docs and the strongest sla. they overlap but serve different buyers. this is the may 2026 comparison with prices from each dashboard.

the matrix

prices change. snapshot is may 1, 2026.

apify: the developer platform

apify is the only one of the three that’s a real platform-as-a-service for scraping. you write a docker container that scrapes some target, push it to apify, and they run it on their infrastructure. they call this an “actor.”

3000+ public actors exist already. amazon scraper, instagram scraper, google maps scraper, linkedin scraper, twitter scraper, facebook ads library scraper, youtube scraper. most are maintained by apify themselves or trusted community devs.

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

# run the official google search scraper actor
run = client.actor("apify/google-search-scraper").call(run_input={
    "queries": "best mobile proxies singapore",
    "maxPagesPerQuery": 3,
    "resultsPerPage": 100,
    "countryCode": "us",
})

# fetch results
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], item["url"])

5 lines of code, no scraper to maintain. you pay the platform usage (compute units + bandwidth) plus the actor’s per-result fee where applicable.

apify pricing is denominated in compute units (cu). 1 cu is roughly 1gb-hour of memory + cpu. a typical google search scrape uses 0.1-0.5 cu. the $49/month starter plan gives you 49 cu, which goes far for hobbyist scraping.

what’s bad: apify’s residential proxy pool is smaller than bright data’s or oxylabs’. for protected sites, you’re better off pairing apify’s compute platform with an external residential proxy. they support this directly in actor inputs.

we cover apify in our web scraping apis for developers 2026 article.

bright data: the data and infrastructure giant

bright data is the largest of the three by revenue and pool size. their proxy network is the deepest, their web unlocker handles the meanest sites, and their dataset catalog is unmatched.

three product lines:

(1) proxy network. residential, datacenter, isp, mobile. all the standard tools.

(2) managed apis. web unlocker, serp api, scraping browser, data collector. these are bright data’s “we’ll do the scraping for you” stack.

(3) datasets. pre-scraped data sold by record. you don’t run a scraper, you just pay for the rows. linkedin profiles, amazon product data, zillow listings, instagram public posts.

import requests

# trigger a managed scrape via web unlocker
resp = requests.get(
    "https://api.brightdata.com/dca/trigger",
    headers={"Authorization": "Bearer YOUR_TOKEN"},
    json={
        "url": "https://www.target-site.com/products/123",
        "render": True,
    },
)

bright data’s strength is breadth + scale. if you’re scraping at million-page-per-day volumes or need 100% success on sites with serious anti-bot, bright data is the lowest-risk pick.

starter plan is $499/month with usage-based billing on top. expensive entry. for under $1000/month spend, you’ll feel the price more than the technical advantage.

we go deep on bright data in our proxy providers ultimate guide.

oxylabs: the enterprise scraping api stack

oxylabs is the cleanest of the three for engineers who want straightforward apis with no marketplace, no datasets, and no actor system. their core scraping products:

(1) web scraper api. send a url, get back html or auto-extracted json.

(2) serp scraper api. send a query, get back parsed search results.

(3) ecommerce scraper api. send a url to amazon/ebay/walmart/etc, get back parsed product json.

(4) real estate scraper api. send a url to zillow/realtor/redfin/etc, get back parsed listing json.

import requests

resp = requests.post(
    "https://realtime.oxylabs.io/v1/queries",
    auth=("USER", "PASS"),
    json={
        "source": "ecommerce_product",
        "url": "https://www.amazon.com/dp/B0CHX1W1XY",
        "parse": True,
    },
)
print(resp.json()["results"][0]["content"])

response includes parsed product fields ready for ingestion. pricing is per request, $0.001-$0.005/req depending on source and volume tier.

oxylabs’ strength is api cleanliness and reliability. their dashboards are fast, their docs are excellent, and their support team is 24/7 with strong sla. for an enterprise data team that wants “we send urls, you give us clean data,” oxylabs is the easiest sell internally.

what’s bad: no marketplace. if you want a tiktok scraper or a youtube scraper, oxylabs doesn’t have one. you’d need to build it yourself using their proxy network.

use case decision tree

(1) you want to scrape a major site (google, amazon, instagram, linkedin) and don’t want to write or maintain a scraper. all three work, but apify’s actor catalog is the deepest. if the actor exists, apify wins on developer time saved.

(2) you want to buy pre-scraped data without running scrapers at all. bright data datasets is the broadest catalog. apify also has dataset listings on their store but volume is smaller.

(3) you scrape protected sites at high volume and need near-perfect success. bright data web unlocker. expensive but the success rate justifies the spend.

(4) you want clean apis with predictable pricing for major ecommerce or real estate sites. oxylabs is the cleanest.

(5) you’re building your own scraper and want a hosting platform that handles concurrency, retries, and storage. apify is the only one of the three. bright data and oxylabs sell apis, not platforms.

(6) you have an enterprise procurement process and need vendor-grade contracts, sla, and account managers. oxylabs and bright data both qualify. apify can but is more startup-coded.

actual cost comparison

pricing varies by use case. some realistic monthly bills based on real customers we’ve talked to:

bright data wins on extreme-volume protected scraping (the unlocker is genuinely cheaper at scale). apify wins on small-to-medium custom scraping where actor reuse pays off. oxylabs wins on clean enterprise spend predictability.

developer experience

apify: best of the three. apify cli, sdk in python and node, actor sdk for building your own, dashboard with logs, dataset viewer, scheduler, alerts. you can ship a custom scraper in an afternoon.

bright data: most surface area, steepest learning curve. multiple products with overlapping features. dashboard is feature-rich but takes time to learn. docs are thorough but scattered.

oxylabs: cleanest of the three for the api-only flow. one endpoint pattern (POST /v1/queries with a source parameter) covers most use cases. minimal cognitive load.

marketplace quality on apify

since apify’s marketplace is the unique selling point, here’s a snapshot of what’s actively maintained vs abandoned:

community actors range from excellent to abandoned. always check last-update date and run count before depending on one.

reliability and uptime

bright data and oxylabs both publish 99.9%+ uptime sla on enterprise plans. real-world data backs this.

apify is at 99.7-99.8% on their compute platform. occasional dataset api hiccups. for non-critical scraping this is fine, for time-sensitive feeds you’d want fallback paths.

if your scraper is mission-critical (real-time pricing for trading, fraud detection feed), bright data or oxylabs are safer. for everything else, apify is plenty.

frequently asked questions

what’s the cheapest of the three for a hobbyist?

apify, by a wide margin. the $5 free monthly credit covers light hobby use. bright data and oxylabs are designed for paying customers.

can i use bright data’s proxies inside apify actors?

yes. apify actors support custom proxy configs. many people use apify for the compute + scheduler + storage and bright data for the proxies.

is apify safer than running scrapers myself?

operationally, yes. they handle retries, error logging, scheduled runs, dataset storage, and monitoring. legally, no. you’re still responsible for what you scrape and how you use the data.

which platform is best for scraping linkedin?

apify has actively maintained linkedin actors. bright data has linkedin in their dataset catalog. oxylabs supports linkedin via the web scraper api but with stricter usage limits. apify is the most flexible.

do any of them solve captchas natively?

bright data’s web unlocker and oxylabs’ web scraper api solve common captchas as part of the managed flow. apify actors integrate captcha solvers via configurable inputs but you bring your own solver budget.

what about smaller competitors like scrapfly or zyte?

different category but overlapping. zyte and scrapfly compete more directly with bright data web unlocker on the api side. neither has apify’s marketplace or bright data’s dataset catalog. for a focused choice between unblocking apis, see our scraperapi vs zyte article.

final thoughts

if you’re a developer or small team looking to ship custom scrapers fast, apify is your platform. if you’re an enterprise that needs the deepest infrastructure and dataset catalog, bright data is the safe pick. if you want clean apis with predictable enterprise sla and don’t need a marketplace, oxylabs is the cleanest.

most production stacks i’ve seen end up using two of the three. apify for custom one-off scrapers, bright data for the heavy unlocking work or pre-scraped datasets. oxylabs for ecommerce-specific apis where their parsing quality saves engineering time. you don’t have to pick just one.