Scrapy vs Apify

Self-hosted control versus a managed platform that bundles scheduling, storage and proxies with the runtime.

Scrapy is the mature asynchronous Python crawling framework — middlewares, pipelines, AutoThrottle and a proxy layer that scales to millions of pages. It is maintained by Zyte / open source, runs on Python 3.9+ · Linux · macOS · Windows, and starts at Free.

Apify is hosted actor platform with 5,000+ prebuilt scrapers, a managed proxy pool, scheduling and dataset storage. It comes from Apify Technologies, runs on Cloud · Node/Python SDK · REST API, and starts at $0 (free tier) · from $49/mo.

Scrapy is dramatically cheaper at steady volume because you supply the compute and buy proxy bandwidth wholesale. Apify wins on time-to-first-dataset and on operations you would otherwise build yourself — cron, retries, dashboards, dataset export and a store of ready-made actors.

We score every scraping tool on five axes that decide real projects: how quickly a new engineer becomes productive, how far the tool scales before it needs replacing, how well it survives anti-bot systems, how good the documentation and community are, and what you get per dollar. Scrapy scores 9.1/10 overall against 8.7/10 for Apify, but the aggregate hides the trade-off that matters to you.

The clearest gaps are on ease of use and anti-bot handling. Read those two rows first; the rest are close enough that team familiarity should decide.

Throughput decides your proxy bill as much as your compute bill: a tool that needs a full browser to read a page transfers ten to thirty times more bytes than one that parses HTML directly, and residential bandwidth is priced per gigabyte.

Scrapy sustains 600 – 3,000 pages/min per worker and uses roughly ~120 MB per worker. Apify sustains Elastic — limited by plan concurrency at roughly Managed. On JavaScript-heavy targets, Scrapy handles rendering like this: None (needs Playwright or a rendering API) Apify: Yes, in browser actors

Scrapy: BSD-licensed. Costs are infrastructure plus whatever proxy network you point it at.

Apify: Usage-credit model: compute units, residential GB and datacenter IPs draw from the plan balance.

Neither list price is your real cost. Add proxy bandwidth for every tool that does not bundle it, add the compute hours for anything that drives a browser, and add the engineering time that a self-hosted stack consumes every month. A framework that is free to license routinely costs more per delivered page than a paid unlocker once residential gigabytes and failed requests are counted honestly.

Proxy strategy is where most scraping projects leak money. Scrapy expects: HTTP, HTTPS and SOCKS5 via downloader middleware; rotating gateways work out of the box Datacenter proxies first, rotating residential per domain once the measured block rate passes a few percent.

Apify expects: Built-in datacenter and residential pools plus bring-your-own proxy URLs Managed pool by default; bring-your-own proxy URLs once volume justifies a direct contract.

Whichever tool you pick, tier your proxy network per domain rather than globally. Start every target on datacenter IPs, promote it to rotating residential when the block rate on that specific domain passes a few percent, use static ISP IPs for anything logged in, and reserve mobile exits for app-only endpoints. Teams that apply one proxy type to every target routinely overpay by five to ten times.

Neither tool is strictly better. The lists below are the differences that changed our recommendation during testing, not feature-sheet trivia.

Scrapy is dramatically cheaper at steady volume because you supply the compute and buy proxy bandwidth wholesale. Apify wins on time-to-first-dataset and on operations you would otherwise build yourself — cron, retries, dashboards, dataset export and a store of ready-made actors.

Choose Scrapy when: Predictable, high-volume crawling where infrastructure engineering time is available and unit cost matters most.

Choose Apify when: Small teams, bursty jobs, or projects that need to ship this week without owning queues, storage and proxy plumbing.

A large share of production stacks run both. Using Scrapy for the bulk of the crawl and Apify for the fraction of domains it handles better is almost always cheaper than forcing one tool to cover every target, because the expensive path only gets used where it earns its price.