Apify occupies an unusual position in web scraping. It is not a no-code scraper you point at a page, and it is not a raw proxy API you glue into your own code. It is a cloud platform for running containerised scraping jobs — called Actors — with a marketplace of 30,000+ prebuilt ones on top, and the whole thing is billed by the compute-hour.
That combination makes it genuinely excellent for one set of users and genuinely frustrating for another. This review covers what it does well, where it hurts, what it costs, and how to tell which group you are in.
Disclosure: this page contains affiliate links. If you sign up through one we may earn a commission at no extra cost to you. It does not change our assessment — the criticisms below are the ones we would give a friend.
What Apify actually is
The unit of work is an Actor: a packaged job that takes JSON input, runs in a container, and writes structured output to a dataset, key-value store or request queue. You can run somebody else's Actor from the Store, or write your own and deploy it.
Around that sit the things that make scraping at scale annoying if you have to build them yourself — a proxy pool, scheduling, webhooks, monitoring, retries, storage, and RAM tiers that scale with your plan. Apify's pitch is that it manages the infrastructure so you only own the extraction logic.
For custom work there is Crawlee, Apify's open-source crawling library, plus SDKs. Crawlee is genuinely good and worth knowing about independently — it is usable off-platform, which meaningfully reduces the lock-in risk of building on Apify.
The Actor Store is the real product
The 30,000+ Actor library is Apify's strongest asset and the honest reason most people choose it. Scraping Google Maps, LinkedIn, Instagram, Amazon or a dozen other awkward targets goes from a multi-week engineering project to picking an Actor, filling in a JSON form and pressing run.
If your requirement is "get me structured data out of a well-known platform", the Store is close to unbeatable and nothing else in the market matches its breadth.
The catch is quality variance, and it is a real one. Many Store Actors are community-maintained rather than built by Apify. When a target site changes its markup, third-party Actors break, and you are waiting on somebody else's maintenance schedule with your pipeline down. Before you build a production dependency on a Store Actor, check its recent update history, its issue tracker and who maintains it. A popular, actively maintained Actor is a reasonable dependency; an abandoned one with 4,000 users is a liability.
Reliability and infrastructure
Apify advertises a 99.95% uptime guarantee, and reliability is consistently the thing users praise in reviews. The managed infrastructure genuinely removes a category of work: proxy rotation, browser fleet management, retry logic and scheduling all come with the platform rather than being your problem.
Integrations are a quiet strength too. The REST API and webhooks are well-documented, and the n8n integration in particular gets repeatedly singled out as seamless — which matters if Apify is one step in a longer automation rather than the whole thing.
What it costs
Apify's plans are Free ($0 with $5 of credit), Starter ($29), Scale ($199), Business ($999) and custom Enterprise. The crucial thing to understand is that the plan fee is a prepaid usage budget, not a subscription. Compute, proxy bandwidth, storage and third-party Actor fees all draw it down, and once it is gone paid plans keep running on pay-as-you-go overage.
Billing is in compute units, where 1 CU is 1 GB of RAM for 1 hour, charged at $0.20/CU on Free and Starter, $0.16 on Scale and $0.13 on Business. You are billed on memory allocated, not used — which is the single most common source of avoidable spend.
Residential proxy at $8/GB is frequently the largest line item at scale, often exceeding compute entirely. We break all of this down, with worked examples, in our dedicated Apify pricing guide.
Where Apify frustrates people
Costs are genuinely hard to forecast
This is the most common complaint and it is fair. Four separate meters — compute, proxy, storage, Actor fees — combine into a number you cannot easily predict before running the job. Competitors selling a flat price per 1,000 records are trivially easy to budget for; Apify is not. You can get to a reliable model, but it takes a week of running your real workload and reading the usage breakdown.
Credits do not roll over
Unused monthly credit expires at the end of the billing cycle. For steady, predictable workloads this is fine. For lumpy usage — heavy one month, quiet the next — it feels punitive, and it means the standard advice to "upgrade for the cheaper rate" is wrong unless your usage genuinely sits near the next tier's credit.
The learning curve is real for custom work
Running a Store Actor is easy. Writing, deploying and debugging your own is a proper engineering task involving the SDK, container builds and the platform's storage model. If your team does not have that capacity, you are effectively buying access to the Store, and you should evaluate it on those terms.
Concurrency is memory-bound, not run-bound
Plans advertise a concurrent-run count, but combined memory is the ceiling you actually hit. On Starter, 64 GB total against a 4 GB Actor gives you 16 real concurrent runs, not the 32 advertised. This surprises people in production.
How it compares to the alternatives
- Bright Data is the enterprise-scale rival, with per-record pricing that is far easier to forecast, a free tier around 5,000 records/month and plans from roughly $499. Better for very large multi-target operations; considerably more expensive to start.
- Octoparse is the no-code choice, from roughly $99/month. Better if you are not a developer and need structured data on a schedule; far less flexible if you are.
- ScrapingBee, from about $49/month, is the simplest possible API to glue into existing code. Note it was acquired by Oxylabs in June 2025.
- Firecrawl has taken the AI and LLM ingestion niche, which is worth a look if your endpoint is a vector store rather than a spreadsheet.
Apify's differentiator against all of them is the Store. If your targets are covered by well-maintained Actors, nothing else gets you to data faster. If you are scraping obscure or bespoke targets and writing everything yourself anyway, the Store advantage evaporates and the comparison comes down to price predictability — where Apify is the weakest of the four.
Who should use Apify
Use it if you need data from well-known platforms and want it this week rather than next quarter; you have developers who can write an Actor when the Store falls short; you are already automating with n8n, Make or similar; or you want to start small, since $29 is the cheapest serious entry point in this category.
Look elsewhere if finance needs a fixed, predictable monthly number; you have no developer capacity at all and need a genuine no-code tool; or you are operating at a scale where per-record pricing from an enterprise vendor would work out cheaper and simpler.
Verdict
Apify is the best general-purpose web scraping platform available in 2026 for teams that have at least some engineering capability, and the Actor Store is a genuine moat that no competitor has replicated. The reliability is there, the tooling is good, and Crawlee being open source means building on it does not trap you.
The pricing model is the price of admission. It is not expensive so much as unpredictable, and going in without understanding compute units, allocated-versus-used memory and the true cost of residential proxy is how people end up with an invoice they did not expect. Read the pricing breakdown before you scale up, not after.
The sensible way to evaluate it costs nothing: the free tier gives you $5 of credit, 25 concurrent runs and no time limit, which is enough to run your actual target and read the real usage numbers. Start on the free tier, run the job you actually care about for a week, and let your own usage data pick the plan.