Why Redis Beats Node.js and Standard DBs for Building a Rate Limiter

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A developer built a rate limiter from scratch after failing an Amazon online assessment that included a rate-limiting question, using the experience to explore why common approaches fall short. Node.js, despite being single-threaded, is asynchronous, meaning two simultaneous requests can bypass in-memory rate limits due to event-loop race conditions at await boundaries. Standard databases like MongoDB or SQL face similar issues through stale reads under MVCC concurrency models, unless expensive row-level locks are applied. Popular packages such as express-rate-limit suffer from a 'boundary burst' flaw, where a fixed-window reset allows up to double the intended request limit within a very short span. Redis addresses these problems using a ZSET data structure that combines a hash map and skip list, enabling O(1) lookups and O(log N) range queries without the costly memory-shift operations of array-based approaches.

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