Caching Strategies

Caching is one of the most powerful tools for improving system performance. Understanding when and how to cache data is essential for system design interviews.

Cache-Aside (Lazy Loading)

The application manages the cache directly. On a cache miss, data is loaded from the database and stored in cache.

Pros: Only requested data is cached Cons: Cache miss is slow (3 round trips); data can become stale

Write-Through

Data is written to cache and database simultaneously.

Pros: Cache is always fresh Cons: Write latency increases; unused data may be cached

Write-Behind (Write-Back)

Data is written to cache immediately, then asynchronously to the database.

Pros: Very low write latency Cons: Risk of data loss if cache fails before flush

Read-Through

Cache sits in front of the database. Application always reads from cache; cache fetches from DB on miss.

Pros: Application code is simpler Cons: First request is always slow

Cache Eviction Policies

• LRU (Least Recently Used) — Evict the item not used for the longest time
• LFU (Least Frequently Used) — Evict the item used least often
• FIFO — Evict in insertion order
• TTL — Evict based on time-to-live