Intermediate10 min readPerformance & Scaling
Cache Patterns
Comparing Cache-Aside, Read-Through, Write-Through, and Write-Back data synchronization models.
What you'll learn
- Read Through Cache
- Write Through Cache
- Write Back (Write Behind)
TL;DR
Comparing Cache-Aside, Read-Through, Write-Through, and Write-Back data synchronization models.
Concept Overview
Cache Strategies define how application layers synchronize memory caches (e.g. Redis) with backend persistent databases. Choosing the right pattern determines data freshness, read latency, and system write speeds.
Key Architectural Pillars
1
Read Through Cache
Application queries cache; on miss, the cache library synchronously fetches from DB, caches it, and returns.
2
Write Through Cache
Application writes to cache and database simultaneously before confirming success.
3
Write Back (Write Behind)
Application writes to cache instantly and returns success; cache writes updates to DB asynchronously in batches.