Redis vs Memcached: Choosing the Right Cache

Memcached and Redis both cache data in memory, and for the specific use case of caching serialized objects with a TTL, either works. The differences become significant when you need anything beyond that.

Memcached — built for maximum throughput on one job

• Memcached was designed from the ground up to be the fastest distributed cache for string key-value pairs — it's multi-threaded, highly optimized for that single use case, and nothing else
• It supports only String values; no data structure operations; no persistence; no pub/sub; no scripting; no replication; no atomic operations beyond INCR/DECR
• Choose Memcached when the only requirement is storing serialized objects with a TTL and maximum throughput is the goal — nothing more

Redis — a data structure server

• Redis is not just a cache — it's a data structure server that supports Strings, Hashes, Lists, Sets, Sorted Sets, and Streams, each with purpose-built atomic operations
• Redis is single-threaded for command execution (multi-threaded for I/O in Redis 6+), which means command ordering is deterministic — INCR on a counter is always atomic, making it safe for rate limiting and distributed counters
• Redis supports persistence (RDB snapshots, AOF log), replication, Cluster mode for horizontal scaling, and pub/sub — making it a complete data platform, not just a cache

Why Redis won

• Redis's richer feature set covers caching, session storage, rate limiting, pub/sub, queues, and leaderboards in one tool — teams avoid running both Redis and a message broker for simple queue needs
• The throughput difference between Redis and Memcached is negligible for most web applications; the operational simplicity of one tool for many purposes has made Redis the default choice

For a Spring Boot application that needs caching: Redis. The spring-boot-starter-data-redis integration handles it, and you'll likely use other Redis features (sessions, rate limiting) in the same application.