Ensuring Data Consistency Between Redis and MySQL: Cache Strategies and Distributed Locks Explained

Maintaining data consistency between Redis cache and MySQL database is a fundamental challenge in modern backend architecture. This guide explores the most common cache update strategies—cache-aside, write-through, write-behind, and refresh-ahead—and analyzes their trade-offs in terms of consistency, performance, and complexity. It also delves into the role of distributed locks (using Redis or ZooKeeper) in preventing race conditions during concurrent writes. Beyond theory, the article discusses real-world failure scenarios such as cache stampedes, stale reads, and partial updates, offering practical mitigation techniques. For backend engineers and system architects building high-throughput applications, understanding these patterns is crucial for designing systems that are both fast and correct. This guide serves as a reference for choosing the right consistency model for your use case, whether you prioritize eventual consistency or strong consistency.