Caching Strategies — Where and How to Cache

Why Cache?

Every layer of a system has a speed hierarchy:

Caching stores expensive results in a faster layer. A DB query taking 10ms served from Redis takes ~0.1ms — 100x faster.

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Cache-Aside (Lazy Loading)

The most common pattern. Application manages the cache explicitly.

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Write-Through

Every write goes to both cache and database simultaneously.

Use when: Read-heavy, can't tolerate stale data

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Write-Behind (Write-Back)

Writes go to cache first, database updated asynchronously.

Use when: Write-heavy, write latency matters

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Cache Eviction Policies

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Cache Stampede Problem

Fix: Use a mutex — only one request fetches from DB, others wait.

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Where to Cache

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Key Takeaway

• Cache-aside is the default — simple, resilient, widely used
• Always set a TTL — unbounded caches grow forever
• Invalidate on write for data that must be fresh
• Watch for cache stampede on high-traffic systems
• Redis is the industry standard for distributed caching