Apify Review: Features, Pricing & Tests

Apify gets reviewed as if it were a scraper API, and that framing misses what it is. It is a web scraping platform: a place to run pre-built scrapers, build your own, schedule them, and store the output, billed by compute rather than per request. The question I get is whether that platform model earns its keep versus a plain request-based API in 2026. This is a single-vendor review: what Apify is, how its pricing works, the features that matter, honest pros and cons with sentiment attributed, and who it fits. Every price and feature below comes from Apify’s own pricing page and documentation in mid-2026, attributed inline, because pricing pages move and review-site numbers go stale fast. If you want the wider category first, start with the web scraping pillar guide.

One disclosure up front: bestscraperapi.com earns affiliate commissions from some of the vendors I write about, including the ChocoData comparison at the end. That does not change the numbers. Pricing comes straight from each vendor’s own page, and I flag every figure I could not verify rather than guessing.

A second note on performance. The speed and reliability figures in this review are approximate, compiled from Apify’s published material plus aggregated public reports. They are not bestscraperapi.com’s own first-hand tests. My independent, like-for-like benchmarks are still in progress; see how we test for the methodology.

What is Apify?

Apify is a cloud platform for running and building web scrapers, organized around a unit it calls an Actor: a serverless program, packaged as a Docker image, that takes structured JSON input and produces structured output. Per Apify’s docs, an Actor is “a serverless program to automate workflows and extract data.” You can run an Actor from the Console, the CLI, the API, or on a schedule, and chain several together into a pipeline. That is the core difference from a request-based scraper API: you are running programs that scrape, not sending one URL at a time to an endpoint.

Two things sit around that core. The first is the Apify Store, a marketplace of pre-built Actors for common targets (e-commerce, social, search, maps) that you run without writing code by filling in an input form. The second is Crawlee, Apify’s open-source scraping library for JavaScript and Python, which you can run anywhere for free and deploy onto the platform when you want hosting, scaling, and proxies. For the engineering context behind that build-versus-buy choice, see scraping without getting blocked.

How much does Apify cost?

Apify uses monthly plans priced by an included usage allowance, and the meter under that allowance is the Compute Unit. The four tiers below are confirmed from Apify’s pricing page in mid-2026. Annual billing carries a roughly 10% discount on the paid tiers.

The included usage is a dollar allowance you spend on compute, proxies, and storage, not a request count. Per the pricing page, unused credits do not roll over and expire at the end of each billing cycle. Free accounts are blocked once they hit the $5 allowance until the next cycle; paid accounts keep running and pay overage at their plan’s CU rate. The headline price tells you little until you convert it into Compute Units for your workload, which is the next section.

How do Apify Compute Units work?

A Compute Unit is the platform’s billing meter: per Apify’s docs, “1 CU = 1 GB of RAM running for 1 hour.” Your cost for running an Actor is its allocated memory multiplied by its runtime, priced at your plan’s CU rate, plus any proxy and storage usage on top. This is the detail that drives the whole cost model, so it is worth working an example.

So a Starter plan’s $29 allowance buys roughly 145 CUs at the $0.20 rate before overage, and how far that goes depends entirely on how much memory your Actors use and how long they run. Residential proxy traffic is billed separately by the gigabyte (from $8/GB on lower tiers down to $7/GB on Business, per the pricing page), and that often dominates the bill on hard anti-bot targets. The practical read: budget Apify by estimating memory times runtime times CU rate, then add proxy gigabytes, rather than by counting requests.

What does the Apify Store cost?

Pre-built Actors in the Apify Store carry their own pricing on top of platform usage, and there are three live models in mid-2026 (plus one being retired). Per Apify’s docs, the models work like this.

The rental model is being sunset, per Apify’s docs: no new rentals are accepted from April 1, 2026, with full retirement and migration to pay-per-usage on October 1, 2026. For pay-per-event Actors, you can set a maximum charge limit when starting a run, which caps spend on an unpredictable target. The takeaway for budgeting: a Store Actor’s listed price and the platform CUs it burns are two separate line items, so read both before you run something at volume.

What features does Apify offer?

Apify bundles the Actor runtime, the Store marketplace, storage, scheduling, proxies, an open-source library, and a REST API. Here is what its documentation confirms exists, by name, in mid-2026.

The proxy layer offers three types per the docs: datacenter (“the fastest and cheapest”), residential (“the least likely to be blocked”), and a Google SERP proxy for localized search results by country and language. The library layer, Crawlee, ships several crawler classes (CheerioCrawler, PlaywrightCrawler, PuppeteerCrawler, and others) for static and JavaScript-heavy pages, which overlaps with what you would otherwise wire up by hand in Scrapy or with BeautifulSoup.

On the API, a run is a POST to the Actor’s runs endpoint, and Apify supports a synchronous variant that waits up to 300 seconds and returns dataset items directly. The pattern below is from Apify’s documented API format; I have not executed it here, so I am not pasting fabricated output.

# Documented request pattern (not run here)
curl -X POST "https://api.apify.com/v2/acts/ACTOR_ID/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "startUrls": [{ "url": "https://example.com" }] }'

If you are wiring this into Python, the official apify-client package handles auth and retries, and drops into the workflow from the Python web scraping guide.

How fast and reliable is Apify?

There is no single Apify speed or success-rate number to quote, because performance depends on which Actor you run, how much memory you give it, and whether you use proxies. That is the honest framing: a platform that runs arbitrary programs does not have one headline latency the way a single-endpoint API does. The figures below are approximate, compiled from Apify’s published material plus aggregated public reports, and are not bestscraperapi.com’s own measurement.

Two caveats before you lean on these. First, more allocated memory speeds an Actor up but burns CUs faster, so speed and cost trade directly against each other here in a way a flat per-request API hides. Second, the run-speed row is approximate, compiled from public reports and vendor material, not a controlled test by me. My independent, same-target benchmark is in progress at how we test; check back for measured numbers rather than trusting any vendor’s self-report.

What are the pros and cons of Apify?

The honest summary is that Apify is the most flexible option on this side of the category, with a marketplace and a real runtime, while the CU billing model asks more of you to predict than a flat per-request price. Sentiment below is attributed: these reflect commonly reported developer experience and Apify’s own documented behavior, not a controlled test by me.

The recurring theme in developer feedback is the trade-off between power and predictability: teams praise the breadth of ready-made Actors and the ability to run their own code, then note that estimating monthly spend takes real effort because it depends on memory, runtime, and proxy traffic rather than a flat rate. The Crawlee library draws consistent praise as a genuinely useful open-source tool even for people who never pay for the platform.

Who is Apify for?

Apify fits teams that want a full scraping platform, not just an endpoint: people who will run pre-built Actors for common sites, build custom scrapers, schedule recurring jobs, and keep results in one place. If your work spans many different targets and you value a marketplace plus the option to write your own code, the breadth is the draw, and the open-source Crawlee library lowers the cost of building. It also suits developers who already use Crawlee locally and want managed hosting, proxies, and scaling without re-architecting.

It fits less well if you want a single, predictable per-request price for one repetitive job, because the CU model and separate proxy billing take effort to forecast, or if your need is narrow enough that a flat-rate API is simpler to reason about. For those cases, compare the per-request economics against a request-priced alternative before committing.

How does Apify compare to ChocoData?

ChocoData is a useful contrast because it sits at the other end of the design space: a request-priced scraper API rather than a compute-priced platform. Both return scraped data and handle proxies and anti-bot for you, but the billing unit and the mental model differ. The comparison below is factual, from each vendor’s own pages in mid-2026.

The practical read: Apify is the broader tool, giving you a runtime, a marketplace, and an open-source library, with billing that scales by compute and proxy usage. ChocoData is the narrower, simpler one, publishing a $19/mo paid entry and a universal endpoint plus 453 dedicated endpoints, per ChocoData’s site in mid-2026, with a flat per-request credit cost that is easier to forecast. If you want a full platform and will use the marketplace or write Actors, Apify covers more ground; if you want one predictable per-request price for structured data from named sites, ChocoData is the simpler pick. Try ChocoData.

One last reminder, because it matters for budgeting: every figure here is what each vendor published in mid-2026, and scraper pricing changes frequently. Confirm the current number on the vendor’s own pricing page, and check whether a plan bills by compute, by request, or by result so you are comparing like with like. For the broader landscape, the web scraping pillar guide and the Scrapy guide cover the free, self-hosted alternatives you can pair with or run instead of a platform.