Token Bucket vs Sliding Window: How APIs Choose the Right Rate Limiting Algorithm

Rate limiting controls how many requests a client can make within a set period, protecting backend capacity, shared resources, and even the clients themselves. The basic fixed-window counter has a well-known flaw: clients can double up requests across window boundaries, effectively bypassing the stated limit. The token bucket algorithm addresses this by maintaining a pool of tokens refilled at a steady rate, allowing short bursts from idle clients while smoothing overall traffic flow. Sliding window counters take a different approach, measuring requests over a rolling time period rather than fixed calendar intervals, which eliminates the boundary-exploit problem at the cost of slightly more complex implementation. Choosing between the two depends on the use case: token bucket suits backend protection with bursty traffic, while sliding window better fits scenarios requiring strict, auditable request counts.