Caching Strategies

Why Caching?

Caching reduces latency, offloads the database, and increases throughput by storing previously computed results.

Common Strategies

Cache-Aside (Lazy Loading)

Application manages the cache directly - read from cache first, on miss read from DB then write to cache.

Read: Cache → miss → DB → write to Cache → return
Write: DB → invalidate Cache

Pros: Only caches data that’s actually used Cons: Cache miss penalty, potential stale data

Write-Through

Write to both cache and DB simultaneously.

Write: Cache + DB (simultaneously)
Read: Cache → always hit (after first write)

Pros: Data always consistent Cons: Higher write latency

Write-Behind (Write-Back)

Write to cache first, async write to DB later.

Write: Cache → async → DB
Read: Cache → hit

Pros: Low write latency Cons: Risk of data loss if cache crashes

Comparison

Strategy	Read speed	Write speed	Consistency	Complexity
Cache-Aside	Medium	Fast	Eventual	Low
Write-Through	Fast	Slow	Strong	Medium
Write-Behind	Fast	Fast	Eventual	High

Cache Eviction Policies

• LRU (Least Recently Used) - Most common
• LFU (Least Frequently Used)
• TTL (Time To Live) - Expire after fixed duration
• FIFO (First In First Out)

Popular Tools

• Redis - In-memory, supports many data structures
• Memcached - Simple, fast, key-value only
• CDN - Cache static assets at edge locations