Apify and Anakin both give developers a way to pull structured data from the web without maintaining scraping infrastructure themselves. Apify does it through a Store of more than 98,000 ready-to-run tools it calls Actors. Anakin does it through a suite of purpose-built products under one API key, from Wire's pre-built site actions to URL scraping, crawling, search, and hosted browsers.
The products overlap on the surface: both scrape pages, crawl domains, and run browsers at scale. The difference that matters shows up on the invoice and in what happens when something quietly breaks. Apify's compute-billed runs cost money even when they fail, and a broken Store Actor can take weeks to get flagged. Anakin charges credits only for successful calls, at a price you know before you send them, and maintains its own integrations.
What Apify does well
Apify launched in 2015, which makes it one of the longer-running platforms in web scraping, and it shows. The Apify Store has a pre-built Actor for nearly every major site: Amazon listings, LinkedIn profiles, Google Maps results, Instagram posts. If a common scraping task exists, someone on Apify has probably already built and published a working Actor for it.
Apify also maintains Crawlee, an open-source scraping library used well beyond the Apify platform itself. Developers who build locally with Crawlee can deploy the same code to Apify's cloud when they need to run it at scale.
For teams that want a pre-built solution and don't mind managing runtime costs, that marketplace depth is a real advantage. It's a big part of why so many teams start there.
Where the billing gets complicated
Apify charges for compute units: one CU equals one GB of RAM running for one hour, priced from $0.20 per CU on the Free and Starter plans down to $0.13 on Business. A lightweight HTTP scrape might cost a fraction of a CU. A browser-heavy Actor running for ten minutes on 2GB of RAM burns roughly 0.33 CU, somewhere around $0.04 to $0.07 per run before any other fees apply. (Apify pricing, October 2026)
That "before any other fees" part is where forecasting gets harder. Most Store Actors now use pay-per-event pricing, where the developer sets a fixed price for events such as starting a run or returning a result, and some pay-per-event Actors charge platform usage on top. A popular community Google Maps scraper, for example, lists pricing from $1.50 per 1,000 scraped places, with separate add-on events for place details, contact enrichment, and reviews (Google Maps Scraper on Apify). The $19 Starter plan includes $19 of prepaid usage, so the price sheet of each Actor you pick matters as much as the plan. (use-apify.com pricing guide)
The bigger issue for anyone trying to forecast a budget: on pay-per-usage Actors and on Actors you write yourself, you don't know what a run will cost until it finishes. Compute units accrue as the Actor runs, and if it fails partway through, you've still paid for the RAM-hours it used getting there. A usage limit in billing caps the total, but it doesn't tell you the number before you hit run.
How Anakin's pricing works instead
Anakin charges credits per successful outcome, not per unit of compute time. You know the cost of an action before you call it, because the price is tied to what the action does, not how long a server happened to run it. If a job fails, it costs nothing: failed scrapes and timeouts are free, and so are cache hits (Anakin pricing). There's no partial charge for compute burned on a run that didn't complete.
This isn't a minor accounting difference. It changes how you plan. A team running thousands of scraping jobs a day can budget against a known per-call rate instead of reconciling a monthly compute bill that swings with how many jobs failed, retried, or ran longer than expected.
Most of Anakin's products also work asynchronously: you submit a job, get a job ID back immediately, and poll for the result or receive a webhook when it finishes. Apify runs can be started asynchronously through its API too, but a pay-per-usage Actor bills its allocated memory for the whole run, so a slow or stuck run keeps adding cost until it finishes or hits its timeout. For a high-throughput pipeline, as opposed to a few scheduled batch jobs, that difference adds up.
Who catches a broken actor first
Apify runs automated tests on every Store Actor daily, checking whether a run with the default input finishes successfully with a non-empty dataset within five minutes. If more than half of the daily test runs over three days fail, the Actor gets flagged "Under maintenance." If it keeps failing, Apify deprecates it automatically, but only after it has been broken for about a month. (Apify help center, Apify docs)
That's the safety net working as designed, and it still leaves a wide gap. A site restructures its layout and a community Actor starts returning empty fields or malformed rows. As long as the default run still produces a non-empty dataset, the daily test can keep passing, and your pipeline can run on degraded data for weeks without a flag, let alone a fix. The job still reports success. Compute units still get billed. The data just isn't right anymore, and nothing in that flow tells you so.
Wire takes a different approach to the same problem: Anakin maintains the integrations it builds. When a target site changes, the endpoint your agent calls stays the same, because the fix happens on Anakin's side, not in a queue waiting on whichever community developer built the Actor you happened to pick. Wire's actions are also built to self-heal: most breaks from a site change get detected and repaired automatically, and an engineer only steps in for the cases the automated fix can't resolve on its own.
Beyond scraping: pre-built actions for agents
Apify's Store is mostly built for reading the web: extracting listings, prices, posts, and profiles. Actors can automate actions on a site too, but each one is a separate program with its own input format, its own pricing, and its own maintainer.
Anakin approaches agent work through Wire, a catalogue of pre-built actions across more than 970 websites. Each action handles the browser rendering, authentication, and structured extraction behind it, so an agent calls an action_id instead of building and maintaining its own Actor. Because every action shares one API shape, one credit balance, and one maintainer, an agent can find and call actions the same way on every site in the catalogue.
Where the catalogues actually overlap
This isn't just an abstract difference. Wire's catalogue and Apify's Store target a lot of the same platforms. As of 25 October 2026, Wire lists 973 sites and 5,279 actions, and a meaningful chunk overlaps directly with popular Apify Store Actors: Amazon (15 actions), Walmart, eBay, Zillow, Airbnb, Reddit, YouTube, GitHub, Etsy, Yelp, Tripadvisor, Booking.com, Indeed, LinkedIn, Instagram, Facebook, Pinterest, and X all show up in both catalogues. (Wire catalogue)
The mechanism is where the two diverge. An Apify actor targeting Amazon opens a Chromium instance, navigates the page, and parses the DOM, which is why it burns compute units per run and can break the moment Amazon changes a CSS selector. Wire's Amazon actions call the same background API Amazon's own frontend uses, so there's no browser involved and nothing to break when the page gets redesigned, only the underlying data contract, which changes far less often than the markup does.
Apify still leads on a shorter list than it used to. Google Maps, Glassdoor, and Crunchbase aren't in Wire's catalogue yet, and Google Maps is one of the most popular Actors in Apify's Store. If your pipeline depends on one of those, Apify is the more complete option today. LinkedIn, Instagram, Facebook, Pinterest, and X were on this list when this comparison first ran. Wire added public-data actions for all five on 8 October 2026, billed from the same credit balance as every other action (Wire social media docs).
That gap is also where the catalogue is moving. Wire's coverage isn't static: it went from 812 sites and 4,361 actions in June 2026 to 973 sites and 5,279 actions on 25 October 2026, about 20% more sites in under five months. A site that isn't covered yet can be requested with a build request: Wire generates the action from a description of the goal, auto-tests it against the live site, and publishes it to the catalogue on success. The list of what only Apify covers gets shorter over time, not longer.
How each platform handles logins
Logged-in access is the other place the two platforms differ. On Apify, reusing a logged-in account across runs usually goes through a community Actor like Login Session, which automates a login and saves the resulting cookies, localStorage, and sessionStorage to a named pool for reuse in other Actors. It works, but the Apify proxy sessions it relies on last at most 24 hours, and the Actor can't get through two-factor authentication or a captcha on its own. (pocesar/login-session on Apify)
Anakin handles this natively instead of through a bolted-on Actor. You save an account once as a named identity, and Wire resolves it inside an encrypted vault at request time. Credentials are AES-256 encrypted at rest and injected at runtime, and the raw secret is never returned by the API. Teams that already keep passwords in 1Password or Azure Key Vault can connect it as an identity source, so Wire reads the secret at sign-in time instead of storing it. Browser Sessions extend the same idea to plain scraping, keeping authenticated state alive between calls instead of forcing every run to log in again.
Anakin vs Apify at a glance
| Anakin | Apify | |
|---|---|---|
| Billing model | Credits per successful outcome | Compute units (RAM x time) plus per-actor fees |
| Cost known before running | Yes | Fixed per-event prices on pay-per-event Actors, but pay-per-usage runs are known only after they finish |
| Cost of a failed job | Zero | Compute units already consumed are still billed (pay-per-usage Actors) |
| Execution pattern | Async: submit, get job ID, poll or webhook | Async runs via API, but pay-per-usage Actors bill allocated memory for the whole run |
| Site coverage overlap | 973 sites and 5,279 actions (25 Oct 2026), incl. Amazon, Walmart, eBay, LinkedIn, Instagram | 98,000+ Actors, incl. the same sites plus Google Maps, Glassdoor, Crunchbase |
| Persistent authenticated sessions | Yes, Browser Sessions | Community Actors such as Login Session, with proxy sessions capped at 24 hours |
| Credential storage | Named identity vault, AES-256 encrypted at rest | Cookies/localStorage in a named key-value store (community Actor) |
| Broken integration detection | Managed, endpoint stays stable when a site changes | Daily tests, flagged after 3 days of mostly failed runs, deprecated after about a month |
| Pre-built action catalogue | Yes, through Wire (973 sites) | Actors can automate actions, each built, priced, and maintained separately |
| Compliance | SOC 2 Type II, ISO 27001:2022 | SOC 2 Type II (Apify, Jan 2025) |
| Entry pricing | Free (300 credits), paid from $19/mo (Pro) | Free ($5 usage/mo), paid from $19/mo (Starter) |
Values are editorial assessments based on available documentation, not independently benchmarked figures.
When Apify is the better fit
If you need a scraper for a specific, well-known site and don't want to write any code, or if that site is one of the ones Wire doesn't cover yet, like Google Maps or Glassdoor, the Store's breadth is hard to beat. For teams comfortable managing a compute-unit budget and running scheduled batch jobs rather than high-throughput pipelines, Apify's model works fine too. Outside Wire's catalogue, Anakin's URL Scraper and Crawl still handle any public page at a credit per page, though without a site-specific pre-built action.
When Anakin is the better fit
If you're building a production pipeline where cost predictability matters, where jobs run continuously rather than on a schedule, or where your target sites overlap with Wire's catalogue, Anakin's model is built for that. Credits per outcome mean your budget scales with what actually succeeds, not with how much compute a job happened to consume trying. And when your agents eventually need to take actions on a platform instead of just extracting from it, that capability is already there.
Frequently Asked Questions
How does Apify pricing work in 2026?
Apify has a Free plan with $5 of monthly usage and paid plans at $19 (Starter), $199 (Scale), and $999 (Business) a month, each including that amount as prepaid usage. Compute is billed in compute units, where one CU is one GB of RAM for one hour, at $0.13 to $0.20 per CU depending on plan. Most Store Actors use pay-per-event pricing set by the Actor's developer, and some also charge platform usage.
Does Anakin charge for failed requests?
No. Credits are deducted only when a request succeeds, so failed scrapes, timeouts, and cache hits are free. Plans start with a free Starter tier of 300 credits, then Pro at $19 a month, Scale at $100, and Business at $500.
Does Wire cover LinkedIn, Instagram, and Google Maps?
Wire added public-data actions for LinkedIn, Instagram, Facebook, Pinterest, and X on 8 October 2026. Google Maps, Glassdoor, and Crunchbase are not in the catalogue yet. A missing site can be requested with a build request, which Wire auto-tests and publishes on success.
What happens when an Apify Store Actor breaks?
Apify tests every Store Actor daily with its default input. If more than half of the daily runs over three days fail, the Actor is marked Under maintenance, and if it keeps failing for about a month it is deprecated. An Actor that still returns a non-empty dataset with wrong fields can keep passing that test.
Can both platforms reuse a logged-in session?
On Apify, the common route is a community Actor such as Login Session, which saves cookies, localStorage, and sessionStorage for reuse but relies on proxy sessions that last at most 24 hours and cannot handle two-factor authentication or captchas. Anakin stores logins as named identities that Wire resolves at request time, and Browser Sessions keep authenticated state alive between scraping calls.
Get started with Anakin and see the pricing model that charges for what worked, not for how long it ran trying.