Caching Strategies: Redis, Memcached & More
Why Caching Is Critical for System Design Interviews
Caching reduces database load by 60-90% and cuts response times from hundreds of milliseconds to single-digit milliseconds. Every system design interview at Google, Meta, and Amazon expects you to incorporate caching. According to Redis Labs benchmarks, Redis handles 1 million+ operations per second with sub-millisecond latency.
Caching is the single most effective technique for improving system performance and is expected in every system design interview answer.
Cache Placement Strategies
- Client-Side Cache — Browser cache, CDN edge cache. Reduces server requests entirely
- CDN Cache — CloudFront, Cloudflare. Serves static and dynamic content from edge locations
- Application Cache — In-process cache (Guava, Caffeine) for hot data. No network hop
- Distributed Cache — Redis, Memcached. Shared across application instances
- Database Cache — Query result cache, buffer pool. Managed by the database engine
Cache Invalidation Patterns
| Pattern | How It Works | Consistency | Best For |
|---|---|---|---|
| Cache-Aside | App reads cache first, loads from DB on miss | Eventual | General purpose |
| Write-Through | Write to cache and DB simultaneously | Strong | Read-heavy, consistency-critical |
| Write-Behind | Write to cache, async flush to DB | Eventual | Write-heavy workloads |
| TTL-Based | Cache expires after time period | Eventual | Frequently changing data |
Redis vs Memcached
Redis supports data structures (strings, hashes, lists, sets, sorted sets), persistence, pub/sub, and Lua scripting. Memcached is simpler with multi-threaded architecture for pure key-value caching. For most interview scenarios, Redis is the preferred choice due to its versatility.
Master caching patterns for your next system design interview with AissenceAI's real-time architecture suggestions.