What cache should I use for API response caching?

For API response caching, the best default choice is usually:

Use Redis if you need shared, fast, production-grade caching

Redis is the most common choice because it is:

• Very fast
• Centralized/shared across app instances
• Supports TTL expiration
• Good for cache-aside patterns
• Easy to use for rate limiting, sessions, and distributed caching too

Good fit when:

• You have multiple servers or containers
• You want cache entries shared across instances
• You need reliable expiration and eviction
• You expect moderate to high traffic

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Use in-memory cache only if the cache is local to one process

Examples: lru-cache in Node.js, Caffeine in Java, Guava cache, etc.

Good fit when:

• Single server or single process
• Very low latency needed
• Cache doesn’t need to be shared
• You can tolerate cache loss on restart

Downsides:

• Each instance has its own cache
• Cache is lost on deploy/restart
• Doesn’t work well in horizontally scaled setups

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Use CDN / reverse proxy cache for public, cacheable API responses

If your API responses are:

• public
• identical for many users
• safe to cache at the edge

then use:

• Cloudflare
• Fastly
• Akamai
• Varnish
• sometimes NGINX caching

This can be better than app-level caching for read-heavy public endpoints.

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A practical recommendation

If you’re unsure, start with:

• Redis for application-level API caching
• CDN caching for public GET endpoints
• In-memory LRU only for per-instance micro-optimizations

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Rule of thumb

• One app instance → in-memory cache is okay
• Multiple app instances → Redis
• Public responses → CDN or reverse proxy
• Very small/simple app → local cache may be enough

If you tell me your stack (Node/Python/Java/etc.), traffic level, and whether the API is public or user-specific, I can recommend a specific cache strategy.