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Platform Architecture: Apify vs Zyte vs Crawlbase (2026)

· 4 min read
Yassine El Haddad
Yassine El Haddad
Software Developer & Automation Specialist

I build production AI agents, web scrapers, and automation pipelines. Most of what I publish here comes from the actual problems they run into: proxies that get banned, anti-bot stacks that fingerprint your client, RAG that drifts when the underlying data moves. Stack: Python, TypeScript, Go, FastAPI, LangChain, Crawlee, Playwright, deployed on AWS, GCP, and Cloudflare.

When teams move scraping from local scripts to cloud infrastructure, they usually end up choosing one of three operating models:

  1. Serverless Orchestration Layers (represented by Apify)
  2. Framework-Specific Hosting (represented by Zyte)
  3. Stateless API Abstraction (represented by Crawlbase)

This comparison focuses on execution model, scaling limits, and practical trade-offs.

1. Apify: Serverless Container Orchestration​

Apify is a Docker-based serverless platform built for async scraping workloads and headless browser runs.

Architectural Advantages​

  • Language Agnosticism: Because extraction logic (called "Actors") runs in generalized Docker containers, teams can deploy Playwright (Node.js), BeautifulSoup (Python), or even compiled Go binaries simultaneously.
  • Storage Decoupling: Apify inherently decouples execution from storage. A volatile container can crash, but the RequestQueue and append-only Datasets persist in the cloud, allowing replacement containers to resume the pipeline instantly via Crawlee.
  • The Component Ecosystem: Apify hosts a public marketplace of over 6,000 community-maintained Actors. A data team can fork an existing Google Maps extraction Actor, inject custom transformation logic, and deploy it to production in hours.

Failure Modes and Constraints​

  • Synchronous Latency: Spinning up a cold Docker container requires 2 to 4 seconds. Apify is designed for batch data extraction (running 50,000 URLs over 2 hours). Using an Apify Actor as a synchronous API proxy to fulfill a real-time user request (under 500ms) will fail catastrophically due to container initialization overhead.

2. Zyte (formerly Scrapinghub): Framework-Specific Hosting​

Zyte is the entity behind the legendary Scrapy Python framework. Consequently, their infrastructure ("Scrapy Cloud") is hyper-optimized for deploying and monitoring Twisted-based asynchronous Python spiders.

Architectural Advantages​

  • Native Scrapy Integration: If your data engineering infrastructure consists of 500 legacy Scrapy spiders, Zyte offers zero-friction CD deployment.
  • Managed Unblocking: Zyte's proprietary Smart Proxy Manager abstracts ban-handling at the middleware layer seamlessly for Python environments.

Failure Modes and Constraints​

  • Ecosystem Lock-in: Scrapy was constructed a decade prior to the dominance of React/Vue Single Page Applications. While Zyte offers Splash and Playwright integrations, coordinating heavy Headless Browsers through Scrapy's Twisted event loop is notoriously brittle compared to modern Node.js ecosystems (like Crawlee).
  • Product Fragmentation: Zyte's billing architecture splits usage across "Scrapy Cloud compute," "Smart Proxy Manager," and discrete APIs, making cost-auditing highly complex at the enterprise scale.

3. Crawlbase (formerly ProxyCrawl): Stateless API Abstraction​

Crawlbase rejects pipeline hosting entirely. It functions purely as a REST API gateway.

Architectural Advantages​

  • Absolute Simplicity: The data engineer maintains all extraction logic locally or on independent AWS instances. To bypass a WAF, the engineer simply sends a GET request to the Crawlbase endpoint passing the target URI. Crawlbase executes the request globally and returns the raw HTML.
  • Zero Infrastructure Overhead: There are no containers to manage and no Dockerfiles to provision.

Failure Modes and Constraints​

  • State Starvation: Because Crawlbase is entirely stateless, tasks requiring complex session persistence (e.g., executing a multi-step OAuth login before clicking a dropdown to scrape an internal dashboard) are virtually impossible. The connection drops once the HTML is returned.
  • Execution Fragility: If the requesting server (your AWS EC2 instance) crashes, pipeline state is destroyed. Crawlbase cannot provide the persistent RequestQueues that Apify natively supports.

Strategic Recommendations​

  1. If deploying modern, memory-intensive Headless Browser clusters (Playwright/Puppeteer) or requiring language flexibility (Python + Node.js): Deploy to the Apify Platform. Its containerization model natively supports the heavy RAM requirements of modern extraction.
  2. If maintaining a massive repository of legacy, text-only Python Scrapy spiders: Deploy to Zyte Scrapy Cloud.
  3. If injecting raw WAF-unblocked HTML directly into existing, hyper-custom local infrastructure: Utilize the Crawlbase API.
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Frequently Asked Questions

Yes. Apify supports generalized Python environments. You can wrap a Scrapy spider inside an Apify Actor template and deploy it directly, gaining access to Apify's scheduling and storage mechanisms.

Crawlbase offers a specific JS rendering endpoint that utilizes headless browsers internally before returning the HTML. However, you cannot inject custom DOM evaluation scripts directly into their browser context like you can with an Apify Actor.

Apify charges for precise Compute Units (RAM x Time) and proxy bandwidth independently. Zyte charges fixed monthly fees for Scrapy Cloud execution units plus separate proxy traffic. Crawlbase utilizes a strict per-request credit system regardless of rendering time.