COMPARE:
Apify or ZenRows for sites that block you
Apify and ZenRows both do getting data from sites that block ordinary requests, and this page puts them on the same seven questions. Mamba Labs builds Apify actors. Page Finder Extractor is ours, it is the third column, and it does not win most of these rows.
If you only read one part
ZenRows is bought for one reason: the target is fighting back. Apify is bought because you want the job to run every night without you. Those are different problems and they are often both true.
Side by side
| Apify | ZenRows | Page Finder Extractor | |
|---|---|---|---|
| What it actually does | Runs a program against the public web on a schedule or on demand, and hands back a dataset. | Fetches a protected page, solving the anti bot layer, and returns the HTML or a parsed result. | Takes a list of domains and a page to look for, then returns the URL and the extracted content. |
| Coverage and hit rate | A few thousand published actors, plus anything you write yourself, which is the part that matters. | Built for the hard targets. It is at its most useful where a plain fetch returns a challenge page. | Any page type a site actually publishes: pricing, careers, security, leadership, integrations. |
| What it costs | Per event or per compute unit, depending on the actor, and it is usually cents per row. | Per request, with the harder modes costing more, in monthly plans by request volume. | Cents per domain, charged on a returned page rather than on a search. |
| How it fits a workflow | An API, a scheduler, webhooks, and a dataset you pull or push onward. Clay calls it as an HTTP step. | An API, a proxy endpoint, and SDKs for the common languages. | One call for the whole list, from Clay or from a script, and finished rows come back. |
| Where the data comes from | The public web, read directly, which means you can see exactly where a field came from. | The live page, fetched through its own anti bot bypass and proxy rotation. | The sites themselves, fetched directly, so the source URL is on every row. |
| What it takes to set up | Running a published actor takes minutes. Writing your own takes a developer. | Minutes, and the tuning afterwards is a matter of which mode a given target needs. | Give it the domains and say which page you want. |
| Where it stops | There is no table, no interface for a list, and no view of your accounts. | No scheduler and no storage. It is one half of a pipeline you still have to write. | It reads pages. Anything behind a login is not something it can reach. |
The same seven questions are asked on every compare page here, in this order, so two of these pages can be read against each other.
What each is actually better at
- Apify wins on what it costs, where the data comes from. A platform for running scrapers and data actors, yours or somebody else's.
- ZenRows wins on what it actually does. A scraping API sold on getting past the protections that block everything else.
- Page Finder Extractor wins on how it fits a workflow. Finds one named page across hundreds of websites and extracts what is on it.
- Nobody wins on coverage and hit rate, what it takes to set up, where it stops. Apify and ZenRows give the same answer on those, and we are not going to invent a difference.
Try them yourself
What is best for you
Try the plain fetch first. Most of the sites in a B2B data job are not defended at all, and paying anti bot prices to read a careers page is money set on fire. When a target does fight back, ZenRows is a focused answer and Apify's own proxy tiers are usually enough before you need it. Neither solves the part that actually takes the time, which is deciding what to extract and keeping the extraction correct when the page changes next quarter.
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