Rate limiting controls the number of API requests a client can make within a defined time window to protect service availability.
Also known as: Throttling, Request Throttling, API Rate Limit
Rate limiting is a technique that restricts the number of API requests a client can make within a specified time window. It protects API infrastructure from overload, ensures fair resource allocation among consumers, and prevents both accidental and intentional abuse of API services.
Rate limiting implementations use algorithms to track and control request flow. The most common approach is the fixed window counter, which resets request counts at regular intervals — for example, allowing 1,000 requests per minute. When the counter reaches the limit, subsequent requests receive an HTTP 429 (Too Many Requests) response until the window resets.
The sliding window algorithm offers smoother rate enforcement by calculating the request count over a rolling time period rather than fixed intervals. This prevents the "burst at window boundary" problem where a client could send 1,000 requests at the end of one window and 1,000 at the start of the next, effectively doubling throughput momentarily.
The token bucket algorithm provides the most flexible approach. A bucket is filled with tokens at a steady rate, and each request consumes one token. When the bucket is empty, requests are rejected. The bucket has a maximum capacity, allowing short bursts above the steady-state rate while still enforcing long-term limits. This accommodates natural traffic patterns where requests arrive in bursts rather than at a constant rate.
Rate limit information is communicated to clients through standard HTTP headers. X-RateLimit-Limit indicates the maximum requests allowed, X-RateLimit-Remaining shows how many requests are left in the current window, and X-RateLimit-Reset indicates when the window resets. Well-implemented clients use these headers to self-regulate their request patterns.
Without rate limiting, a single misbehaving client can monopolize API resources, degrading performance for all other consumers. This is true whether the overload is accidental (a bug creating an infinite request loop) or intentional (a denial-of-service attack). Rate limiting is the primary defense against both scenarios.
For API businesses, rate limiting is directly tied to pricing strategy. Free tiers might allow 100 requests per day, while premium tiers offer 10,000 requests per minute. This tiered approach enables API providers to serve diverse customer segments while ensuring that resource consumption aligns with revenue.
Rate limiting also protects downstream dependencies. An API that queries a database or calls external services for each request must limit incoming traffic to prevent cascading failures in its own infrastructure. Without rate limiting, a traffic spike could overwhelm databases, exhaust connection pools, or trigger circuit breakers throughout the system.
All APIVult APIs implement rate limiting aligned with subscription tiers, ensuring consistent performance for all consumers. Rate limit headers are included in every response, enabling your applications to implement intelligent retry logic and request pacing. APIVult's documentation for each API — such as SanctionShield AI and FinAudit AI — specifies the exact rate limits for each pricing tier, so you can plan your integration accordingly.