Write-through

Every write goes to the cache and the database together, so the cache is always fresh. Writes become slower, and data that is written but never read still occupies memory.

Where it shows up in real systems

  • In-memory cache

    The hit ratio depends on how much of the working set fits in memory, the TTL and the eviction policy. If the cache goes down or is flushed, every read falls on the database at once: plan for that stampede. Write-behind is fast but loses writes if a node dies without a replica.

    In production: Redis (Amazon ElastiCache, Azure Cache), Valkey, Memcached, Dragonfly

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