Apify Review (2026): Pricing, Features, Pros & Cons

Apify is the largest web scraping platform in the world, and also the one most likely to surprise you on the invoice. You get 30,000+ ready-made scrapers, managed proxies, scheduling and storage — but you pay for compute time and bandwidth rather than results, which makes the true cost genuinely hard to predict before you run anything. This review covers what it does well, what it actually costs, and where the money goes.

What is Apify?

Apify is a cloud platform for running, building and scaling web scrapers and browser automation. Its core unit is the Actor — a containerised program that takes structured input, runs on Apify's infrastructure, and writes results to a dataset. You can run someone else's Actor, fork it, or write your own.

That marketplace model is what separates Apify from a scraping API. Instead of one endpoint that returns page content, you get a catalogue of 30,000+ purpose-built scrapers — Google Maps, Instagram, Amazon, LinkedIn, TikTok, Zillow — each maintained by its developer and each already solving that site's specific defences. For a target that someone has already built for, you go from need to running job in minutes.

Apify pricing in 2026

Apify has four published tiers plus Enterprise: Free at $0 with $5 of credits, Starter at $19/month, Scale at $199/month, and Business at $999/month. Annual billing saves 10% across the paid plans. What separates the tiers is concurrency, memory ceiling and support — not a bigger credit multiplier.

The credit model is unusual — and worth understanding

Here is the thing most reviews skip: on every paid tier, your subscription buys exactly its own value in platform credits. Nineteen dollars buys $19 of usage. Nine hundred and ninety-nine buys $999. There is no volume bonus in the allowance itself.

So what does the extra money buy? Three things: concurrency (5 runs on Free up to 256 on Business), a memory ceiling (16 GB up to 512 GB), and support. The volume discount is real, but it is hidden in the compute rate rather than the credit grant — compute runs $0.13 to $0.20 per compute unit depending on tier, so heavy users pay roughly a third less per unit of work than someone on the entry plan.

You aren't buying credits on Apify. You're buying the right to spend them faster, in parallel, on bigger machines.

That framing matters when you're choosing a tier. If a job is slow because it's rate-limited by the target site rather than by your concurrency, upgrading buys you very little. If you're running fifty scrapers a night and queuing, it buys you everything.

What it actually costs to run

Apify meters four things: compute, storage, data transfer and proxies. Compute is billed in compute units, where 1 CU equals 1 GB of RAM for one hour, at $0.13–$0.20 per CU.

The practical consequence is that your bill tracks how long pages take to render, not how many you collect. A lightweight HTTP scraper on 1 GB of RAM chewing through simple pages is extraordinarily cheap. The same page count through a headless browser at 4 GB, waiting on JavaScript, costs several times more for identical output.

And then there is the line item that catches people out. Residential proxy traffic runs $7–8 per GB. On a site that demands residential IPs, bandwidth frequently costs more than the compute it supports — a crawl pulling half a megabyte per page burns roughly $3.75 per thousand pages in proxy alone, before a single compute unit is counted. Datacenter proxies are far cheaper at $0.60–$1 per IP beyond the included allotment, but plenty of targets reject them outright.

The Actor Store

The Store is Apify's strongest asset. With 30,000+ Actors covering effectively every commonly scraped site, the answer to "has someone already solved this?" is usually yes — and that collapses days of reverse-engineering into a form you fill in.

The trade-off is that a marketplace is not a curated catalogue. Actor quality varies considerably: some are maintained daily by their authors and survive site redesigns within hours; others were published two years ago and quietly broke. Before you build a pipeline on a third-party Actor, check its last update date, its run count and its issue history. Treat a popular, recently-updated Actor as production infrastructure and an obscure one as a starting point to fork.

Pricing on Store Actors varies too — some are free to run and cost only the platform usage they consume, others carry a rental or per-result fee on top. That is worth reading before your first run, not after.

Building your own Actors

If nothing in the Store fits, Apify's own tooling is genuinely good. Crawlee — its open-source crawling library for JavaScript and Python — handles request queues, retries, session rotation, browser fingerprinting and concurrency control, and it is the part of the stack most engineers end up praising.

Crucially, Crawlee runs anywhere. You can develop locally, deploy to Apify for the managed infrastructure, and move off later without rewriting your scraper. That materially reduces lock-in compared with platforms whose SDK only runs on their cloud, and it is a reasonable answer to the pricing unpredictability: the code is portable even when the hosting is not.

Publishing your own Actor to the Store also lets you monetise it, which turns the platform into a distribution channel rather than just a host.

Anti-blocking and proxies

Apify bundles the infrastructure that makes scraping actually work at scale: residential, datacenter and SERP proxies, CAPTCHA handling, browser fingerprinting and session rotation, all managed rather than assembled.

This is the strongest practical argument for the platform. Anyone who has maintained their own proxy pool and fingerprint rotation knows it is a permanent, unglamorous engineering cost. Apify absorbs it. The catch, as above, is that residential bandwidth is metered aggressively — so the feature that makes hard sites possible is also the feature most likely to dominate your bill.

Apify for AI agents

Apify ships an MCP server, which lets agents and tools that speak Model Context Protocol discover Actors, start runs and read datasets directly. In practice that means an AI agent can reach for one of 30,000 scrapers as a tool rather than being handed a single generic fetch endpoint.

It is a genuinely well-judged move. The hard part of giving an agent web access is not fetching a page — it is fetching a structured result from a defended site, which is exactly what the Actor catalogue already encodes. If you are building agents that need real-world data, this is the most compelling reason to look at Apify over a plain scraping API.

Where Apify falls short

Three weaknesses are worth stating plainly. Cost forecasting is the big one — usage-based billing across four separate meters means you cannot confidently answer "what will this crawl cost?" until you have run it. For agencies quoting fixed-price work, that is a real operational problem.

Second, the learning curve is steeper than a single-endpoint API. Actors, datasets, key-value stores, request queues and compute units are all concepts you must absorb before the platform makes sense. If you just want the text of a page, that is a lot of ceremony.

Third, the $5 free tier goes quickly on anything browser-based. It is enough to validate that an Actor works, not enough to complete a meaningful crawl — so budget for a paid month as part of evaluation.

Who should use Apify?

• Teams scraping many different sites — the Store's breadth is unmatched, and it is the whole reason to be here.
• Engineers building custom crawlers at scale — Crawlee plus managed proxies and scheduling is a strong, low-lock-in stack.
• AI agent builders — the MCP server turns 30,000 scrapers into agent tools.
• Anyone facing hard anti-bot defences — the managed proxy and fingerprinting layer is worth paying for.

It is a poorer fit if you need predictable flat-rate costs, if you only ever scrape a handful of simple sites, or if all you want is clean page text for a language model — that last job is served better by a per-page API, which we cover in our Apify vs Firecrawl comparison.

Getting started: zero to first dataset

The fastest useful path through Apify is deliberately not "write a scraper". It is four steps, and it takes about ten minutes:

1. Search the Store for your target site before anything else. Filter by recent updates and high run counts — a maintained Actor is worth more than a clever one.
2. Run it once on the free tier with a deliberately small input: ten URLs, or a maxItems cap. The goal is a usage reading, not data.
3. Open the run's usage breakdown and read the split between compute, data transfer and proxy. This is the number that should decide your plan, and it is the step almost everyone skips.
4. Multiply out to your real volume, then add headroom for retries and failed runs, which are billed like any other.

Only if no Actor fits should you reach for Crawlee and write your own. Forking an existing Actor is usually faster than starting from scratch, because the input schema, proxy configuration and output shape are already defined.

What happens to your data

Every Actor run writes to a dataset, a structured, paginated result store you can export as JSON, CSV, Excel or XML, or read through the API. Alongside it sit key-value stores for files and screenshots, and request queues that manage crawl state across runs and let a job resume rather than restart.

That separation is one of Apify's quieter strengths: results persist independently of the run that produced them, so a crashed job does not cost you the rows it already collected. Scheduling is built in for recurring crawls, and webhooks fire on run completion or failure, which is what you want for piping results into a warehouse or triggering downstream jobs.

Storage is metered like everything else, so datasets you never delete quietly accrue cost. Set a retention policy early if you are running daily crawls.

Verdict

Apify is the most capable web scraping platform available, and the Actor Store is a genuine moat — nothing else gets you from "I need data from this site" to a running job as fast. Crawlee is excellent, the anti-blocking infrastructure is worth real money, and the MCP server makes it unusually well positioned for agent work.

The reservation is billing. Paying for compute time and bandwidth rather than results means the platform is cheapest exactly where scraping is easiest, and most expensive where you need it most. Go in with a metered test run and a budget alert, and it is excellent. Go in assuming a $19 plan covers $19 of intuition, and it will not.

Try Apify free →

$5 free credits monthly, no card required · Paid plans from $19/month