COMPARE:
Apify or ScrapingBee for scraping websites
Apify and ScrapingBee both do getting content out of a list of company websites, and this page puts them on the same seven questions. Mamba Labs builds the Apify actors here, Page Finder Extractor included, and the page says where it is the wrong answer.
If you only read one part
ScrapingBee fetches one page and hands you the HTML. Apify runs the whole job and stores the result. If you already have the code, you want the fetcher. If you do not, you want the platform.
Dimension by dimension
| Apify | ScrapingBee | 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 URL through rotating proxies with a headless browser, and returns the rendered page. | 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. | General purpose fetching, with a handful of prebuilt extractors for search and for retail. | 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 API credit, and a credit costs more when the request needs JavaScript rendering or a premium proxy. | 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. | One endpoint. Everything else is your own code around it. | 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, rendered, so what you get is what a browser would have seen. | 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. There is one key and one URL parameter set to learn. | 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. | It fetches. Scheduling, storage and the shape of the extracted data are all yours to build. | 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.
Who wins what
- Apify wins on what it costs, where the data comes from. A platform for running scrapers and data actors, yours or somebody else's.
- ScrapingBee wins on what it takes to set up, where it stops. One API call that fetches a page, renders it and hands back the HTML.
- Page Finder Extractor wins on what it actually does. Finds one named page across hundreds of websites and extracts what is on it.
- Nobody wins on coverage and hit rate, how it fits a workflow. Apify and ScrapingBee give the same answer on those, and we are not going to invent a difference.
Where to get them
The honest answer
A developer with a working scraper should take ScrapingBee, because a fetching API is exactly the missing piece and a platform is not. A team without that code should take Apify, where the scheduler, the storage, the retries and often the scraper itself already exist. The cost comparison is not per request against per compute unit. It is per request plus the hosting, the queue and the maintenance you now own, against a published actor somebody else keeps working.
Some of the links on this page are affiliate links.