How does Firecrawl compare to Apify for web scraping?

When choosing a web scraping solution, developers often compare Firecrawl and Apify as both offer powerful data extraction capabilities. However, these tools serve different use cases and have distinct approaches to web scraping. This comprehensive guide compares Firecrawl and Apify across key dimensions to help you make an informed decision.

Overview of Firecrawl and Apify

Firecrawl is a modern API-first web scraping service that specializes in converting web pages into clean, LLM-ready markdown and structured data. It handles JavaScript-rendered content, provides intelligent data extraction, and offers a simple API interface for developers who need quick, reliable data extraction.

Apify is a comprehensive web scraping and automation platform that provides a cloud-based infrastructure for running web scrapers at scale. It offers a marketplace of pre-built actors (scraping tools), custom actor development, scheduling, proxy management, and extensive workflow automation capabilities.

Key Differences

1. Approach and Philosophy

Firecrawl focuses on simplicity and developer experience: - API-first design with straightforward endpoints - Automatic handling of JavaScript rendering - Built-in conversion to markdown for AI/LLM applications - Minimal configuration required

Apify emphasizes flexibility and scalability: - Platform-based approach with actor ecosystem - Extensive customization through code - Full control over scraping logic - Enterprise-grade infrastructure

2. Ease of Use

Firecrawl is designed for quick implementation:

from firecrawl import FirecrawlApp

app = FirecrawlApp(api_key='your_api_key')

# Scrape a single page
result = app.scrape_url('https://example.com')
print(result['markdown'])

# Crawl entire website
crawl_result = app.crawl_url('https://example.com', {
    'crawlerOptions': {
        'maxDepth': 2,
        'limit': 10
    }
})

Apify requires more setup but offers greater control:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
    token: 'your_api_token',
});

// Run a pre-built actor
const run = await client.actor('apify/web-scraper').call({
    startUrls: [{ url: 'https://example.com' }],
    pageFunction: async ({ page, request }) => {
        const title = await page.title();
        const content = await page.$eval('body', el => el.textContent);
        return { title, content, url: request.url };
    },
    maxRequestsPerCrawl: 10,
});

// Retrieve results
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

3. Features Comparison

| Feature | Firecrawl | Apify | |---------|-----------|-------| | JavaScript Rendering | ✅ Built-in | ✅ Built-in | | Markdown Conversion | ✅ Native | ❌ Requires custom code | | AI/LLM Integration | ✅ Optimized | ⚠️ Manual implementation | | Pre-built Scrapers | ❌ Not applicable | ✅ Extensive marketplace | | Custom Scrapers | ⚠️ Limited | ✅ Full flexibility | | Proxy Management | ✅ Included | ✅ Advanced options | | Scheduling | ⚠️ Basic | ✅ Advanced | | Data Storage | ⚠️ API response | ✅ Datasets, key-value stores | | Webhooks | ✅ Yes | ✅ Yes | | Monitoring | ⚠️ Basic | ✅ Comprehensive |

4. Pricing Models

Firecrawl Pricing: - Pay-per-use model based on credits - Credits consumed per page scraped - Simple, predictable pricing - No infrastructure costs

Apify Pricing: - Platform usage based on compute units - Actor runtime charges - Proxy and storage costs separate - Free tier available for testing

For simple scraping tasks, Firecrawl tends to be more cost-effective. For large-scale operations running continuously, Apify's infrastructure may provide better value.

5. Use Case Suitability

Choose Firecrawl when you need:

• Quick data extraction from modern websites
• Content for AI/LLM applications
• Simple API integration
• Minimal maintenance overhead
• Clean markdown output
• Fast time-to-market

Example Firecrawl use case:

from firecrawl import FirecrawlApp

app = FirecrawlApp(api_key='your_api_key')

# Extract structured data for AI processing
result = app.scrape_url('https://example.com/article', {
    'formats': ['markdown', 'html'],
    'onlyMainContent': True
})

# Feed directly to LLM
markdown_content = result['markdown']
# Use with OpenAI, Claude, etc.

Choose Apify when you need:

• Complex, multi-step scraping workflows
• Large-scale data extraction (millions of pages)
• Custom scraping logic and browser automation
• Scheduled recurring scraping jobs
• Integration with multiple data sources
• Advanced proxy rotation and session management

Example Apify use case:

import { Actor } from 'apify';
import { PuppeteerCrawler } from 'crawlee';

await Actor.init();

const crawler = new PuppeteerCrawler({
    async requestHandler({ page, request, enqueueLinks }) {
        // Handle authentication
        await page.type('#username', 'user');
        await page.type('#password', 'pass');
        await page.click('#login');
        await page.waitForNavigation();

        // Extract data after login
        const data = await page.evaluate(() => {
            return {
                items: Array.from(document.querySelectorAll('.item')).map(el => ({
                    title: el.querySelector('.title').textContent,
                    price: el.querySelector('.price').textContent,
                })),
            };
        });

        // Save to dataset
        await Actor.pushData(data);

        // Enqueue next pages
        await enqueueLinks({ selector: '.pagination a' });
    },
    maxRequestsPerCrawl: 100,
});

await crawler.run(['https://example.com/products']);
await Actor.exit();

6. JavaScript Rendering Performance

Both platforms handle JavaScript-rendered content effectively, but with different approaches:

Firecrawl automatically detects and renders JavaScript content without configuration. It uses headless browsers under the hood optimized for speed.

Apify gives you full control over browser automation with Puppeteer or Playwright, allowing you to handle AJAX requests and complex interactions.

7. Data Export and Integration

Firecrawl: - Returns data directly via API - JSON and markdown formats - Webhook notifications for crawls - Requires custom storage implementation

Apify: - Built-in datasets with multiple export formats (JSON, CSV, XML, RSS) - Integration with cloud storage (AWS S3, Google Cloud Storage) - Direct integration with Google Sheets, Slack, Zapier - Key-value store for metadata

8. Developer Experience

Firecrawl Developer Experience:

# Install and use in minutes
npm install @mendable/firecrawl-js

# or
pip install firecrawl-py

Simple API with minimal learning curve. Perfect for developers who want to focus on their application rather than scraping infrastructure.

Apify Developer Experience:

# Install Apify CLI
npm install -g apify-cli

# Initialize new actor
apify create my-scraper

# Develop locally
apify run

# Deploy to cloud
apify push

Steeper learning curve but offers professional development workflow with local testing, version control, and deployment pipelines.

9. Handling Dynamic Content

Both platforms excel at dynamic content, but implementation differs:

Firecrawl handles it automatically:

result = app.scrape_url('https://spa-website.com', {
    'waitFor': 5000  # Wait for JavaScript to load
})

Apify provides granular control:

await page.waitForSelector('.dynamic-content');
await page.waitForFunction(() => {
    return document.querySelectorAll('.item').length > 10;
});

This level of control is essential when you need to handle timeouts precisely or wait for specific conditions.

10. Scalability and Infrastructure

Firecrawl: - Managed infrastructure - Automatic scaling - No server maintenance - Limited to API rate limits

Apify: - Dedicated compute resources - Custom scaling configurations - Full control over concurrency - Enterprise-grade reliability

Performance Benchmarks

For a typical e-commerce product page scraping task:

Firecrawl: - Average response time: 2-4 seconds - Concurrent requests: Limited by plan - Success rate: ~98% for standard websites

Apify: - Average response time: 3-6 seconds (with full browser) - Concurrent requests: Configurable (up to thousands) - Success rate: ~95-99% depending on configuration

Migration Between Platforms

If you're considering migrating from one platform to another:

From Apify to Firecrawl: - Best for simplifying architecture - Reduces maintenance overhead - May lose advanced features - Quick migration for simple scrapers

From Firecrawl to Apify: - Enables more complex workflows - Provides better control - Allows custom scraping logic - Requires more development effort

Conclusion

Firecrawl is ideal for developers who need: - Fast implementation - AI/LLM-ready data - Simple scraping tasks - Minimal maintenance

Apify is better suited for: - Complex scraping projects - Large-scale operations - Custom workflow requirements - Enterprise deployments

For many projects, a hybrid approach works best: use Firecrawl for straightforward data extraction and Apify for complex, large-scale scraping operations that require custom logic and extensive automation.

Both platforms are excellent choices, but your specific requirements—complexity, scale, budget, and technical expertise—should guide your decision. Consider starting with Firecrawl for quick wins, then evaluate Apify if you need more advanced capabilities as your project grows.