How do web scraping APIs handle rate limiting and API quotas?
TL;DR
Web scraping APIs use two types of limits: rate limits (requests per minute) control speed, while quotas (total credits/pages) control volume. APIs return 429 status codes when limits are exceeded. Implement retry logic with exponential backoff, batch requests efficiently, and monitor usage to avoid hitting limits.
How do web scraping APIs handle rate limiting and API quotas?
Web scraping APIs manage access through rate limits and quotas. Rate limits control how many requests you can make per minute—preventing server overload and ensuring fair usage. Quotas limit total usage over longer periods through credits or page counts. When you exceed limits, APIs return 429 errors. Firecrawl’s rate limits vary by plan, with concurrent request limits determining actual throughput.
Rate limits vs quotas
Rate limits restrict requests per minute (RPM). Free tier might allow 5 RPM, while enterprise allows 100+. This prevents sudden traffic spikes that could impact service. Quotas limit total usage—500 pages for free tier, 3,000 for hobby, unlimited for enterprise. Credits deduct from your quota with each successful request.
The real bottleneck is concurrent requests—how many scrapes can run simultaneously. Higher concurrency means faster total throughput even with the same rate limit.
Handling 429 rate limit errors
When you hit rate limits, the API returns a 429 status code. Implement retry logic with exponential backoff—wait 1 second, then 2, then 4, before retrying. This prevents overwhelming the API while ensuring your request eventually succeeds.
Best practice: add delays between batches, process URLs in smaller groups, and monitor response headers for rate limit information. Some APIs include headers showing remaining quota and reset times.
Credit-based billing systems
Modern scraping APIs use credits instead of hard request counts. Each operation consumes credits based on complexity—simple scrape costs 1 credit, JavaScript rendering might cost 2-3, structured extraction costs more. This aligns pricing with actual resource usage.
Failed requests typically don’t consume credits. If a scrape fails due to target site issues or rate limits, you’re not charged—ensuring fair billing.
Optimizing for limits
Request only needed formats (markdown vs markdown+html+screenshot) to reduce processing. Use caching for repeated URLs—many APIs cache results for hours or days. Batch similar requests together and use asynchronous processing for large jobs.
Monitor your usage dashboard to track consumption patterns and avoid unexpected quota exhaustion. Set up alerts when approaching limits.
Key Takeaways
Web scraping APIs use rate limits (requests per minute) and quotas (total credits) to manage access fairly. Implement retry logic with exponential backoff for 429 errors. Credit-based systems charge based on resource usage, not just request count. Optimize by requesting only needed data, caching results, and batching requests. Monitor usage to avoid hitting limits unexpectedly.
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