Apify vs Scrapy 2026: Which Web Scraping Tool Should You Use?
Scrapy is the mature Python web crawling framework. Apify is a cloud platform (with Crawlee as its open-source framework) that handles infrastructure, scaling, and storage on top of Node.js.
They're not direct competitors — Scrapy is a code framework, Apify is a full platform — but teams frequently choose between them. This comparison covers where each excels.
Quick Summary
| Scrapy | Apify | |
|---|---|---|
| Language | Python | Node.js (Crawlee) |
| Type | Framework | Cloud platform + open-source framework |
| Setup | Local install | Managed cloud, CLI |
| JavaScript rendering | Via middleware | Native (PlaywrightCrawler) |
| Proxy rotation | Manual config | Built-in |
| Storage | Manual (CSV, DB) | Built-in Dataset, KV store |
| Scheduling | External (cron) | Built-in scheduler |
| Scaling | Self-managed | Managed |
| Pricing | Free | Free tier + usage |
| Learning curve | Medium | Low–medium |
Scrapy: Strengths
1. Python ecosystem. If your team is Python-first, Scrapy integrates directly with pandas, SQLAlchemy, Celery, and the entire Python data stack.
2. Mature and battle-tested. Scrapy has been in production since 2008. There are thousands of community spiders, extensions, and middleware packages.
3. Full control. Every request pipeline stage is configurable — item pipelines, downloader middleware, spider middleware. Nothing is hidden.
4. Free and self-hostable. Zero licensing cost. Deploy on any VM.
import scrapy
class ProductSpider(scrapy.Spider):
name = "products"
start_urls = ["https://books.toscrape.com/"]
def parse(self, response):
for book in response.css("article.product_pod"):
yield {
"title": book.css("h3 a::attr(title)").get(),
"price": book.css(".price_color::text").get(),
"rating": book.css(".star-rating::attr(class)").get().split()[-1],
}
next_page = response.css("li.next a::attr(href)").get()
if next_page:
yield response.follow(next_page, self.parse)
Scrapy + Playwright:
pip install scrapy-playwright
playwright install chromium
class JsSpider(scrapy.Spider):
name = "js_page"
def start_requests(self):
yield scrapy.Request("https://spa.example.com", meta={"playwright": True})
def parse(self, response):
yield {"content": response.css(".data::text").get()}
Apify (Crawlee): Strengths
1. JavaScript rendering out of the box. PlaywrightCrawler handles SPAs, dynamic content, and login flows with no middleware configuration.
2. Built-in infrastructure. Proxy rotation, request deduplication, persistent queue, dataset storage, scheduling — all available with zero boilerplate.
3. Cloud deployment in one command. apify push deploys your scraper to managed infrastructure with auto-scaling, monitoring, and logs.
4. No-code options. 2,000+ pre-built Actors in the Apify Store cover Amazon, Instagram, LinkedIn, Google Maps, and more — without writing code.
import { CheerioCrawler } from 'crawlee';
import { Actor } from 'apify';
await Actor.init();
const crawler = new CheerioCrawler({
async requestHandler({ $, enqueueLinks }) {
const products = [];
$("article.product_pod").each((_, el) => {
products.push({
title: $(el).find("h3 a").attr("title"),
price: $(el).find(".price_color").text(),
});
});
await Actor.pushData(products);
await enqueueLinks({ selector: "li.next a" });
},
});
await crawler.run(["https://books.toscrape.com/"]);
await Actor.exit();
Head-to-Head: Key Scenarios
Scenario 1: Python data science team
Winner: Scrapy. Python is already in the stack. Scrapy items flow directly into pandas DataFrames or SQLAlchemy inserts.
Scenario 2: Dynamic SPA with login
Winner: Apify/Crawlee. PlaywrightCrawler with useSessionPool: true handles this cleanly. Scrapy needs scrapy-playwright middleware and more configuration.
Scenario 3: Large-scale cloud deployment
Winner: Apify. Managed proxies, auto-scaling, and built-in storage make production deployment straightforward. Scrapy requires a Scrapy Cloud subscription (paid) or custom infrastructure.
Scenario 4: Quick scrape of a single site
Winner: Scrapy (Python) or Crawlee (JS) — both fine. Neither has a clear edge for a single-site project.
Scenario 5: No-code/low-code business users
Winner: Apify. The Apify Store's pre-built Actors cover most common targets. Scrapy is code-only.
Scenario 6: GDPR/compliance-strict environment
Winner: Self-hosted Scrapy. Full control over where data goes. Apify stores data on Apify's servers (EU storage available, but external).
Pricing Comparison
| Scrapy | Apify | |
|---|---|---|
| Framework | Free | Free (Crawlee) |
| Cloud hosting | Zyte (formerly Scrapy Cloud): from $25/month | Apify cloud: $5/month free, then $49/month |
| Storage | Your own database | Included in Apify |
| Proxy | Your cost | Apify Proxy included |
Decision Framework
Use Scrapy if:
- Your team is Python-only
- You need deep integration with Python data tools
- You're self-hosting on your own infrastructure
- You want maximum control over every request pipeline step
Use Apify if:
- Your project is JavaScript-heavy
- You want cloud deployment without managing servers
- You need scheduling, storage, and proxy rotation out of the box
- You want to reuse pre-built Actors for common targets
- You're building on Node.js / the Crawlee framework
