Write-Through Cache
Every write goes to the cache and the backing database synchronously in a single operation, ensuring the cache is always consistent with the database.
In write-through caching, the application writes to the cache, and the cache synchronously writes to the database before confirming the operation. This guarantees that the cache and database are always in sync -- no stale data, no inconsistency window. The cost is higher write latency since every write must complete two operations (cache + database) before returning. Write-through is often paired with read-through to create a fully transparent caching layer.
Read/Write Pattern
Writes go to the cache, which synchronously persists to the database before acknowledging. Both stores are always in sync. Reads typically use read-through or cache-aside.
Consistency
Strong consistency for the write path. After a write completes, any subsequent cache read returns the latest value. Concurrent writers can cause ordering issues that require serialization or versioning to resolve.
Failure Mode
If the database write fails, the cache is not updated and the error propagates to the application -- no inconsistency. If the cache fails after a successful database write, the cache may hold stale data; invalidation or retry is needed. Overall data loss risk is zero since writes are always persisted.
Likely Follow-Up Questions
- What is the write latency impact of write-through versus write-behind?
- How do you handle the case where the database write succeeds but the cache update fails?
- When would you pair write-through with read-through versus cache-aside?
- How does write-through interact with database transactions?
- Why might write-through cause cache pollution, and how would you mitigate it?
Source: editorial — Synthesized from standard distributed systems caching literature and production engineering best practices.