What characterizes Write-Through caching?

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Multiple Choice

What characterizes Write-Through caching?

Explanation:
Write-Through caching updates both the cache and the backing store (usually a database) at the same time when a write occurs. This means the write is performed synchronously across both places, so the cache and the database stay in sync and subsequent reads can rely on the most up-to-date value being available in the cache. The trade-off is that write latency includes the time to write to both stores, but you gain strong consistency because no stale data can be read from the cache after a write. Why the other ideas don’t fit: a setup where writes are asynchronous to the database describes Write-Behind, which can lead to temporary inconsistency between cache and storage. A model where only reads are cached loses the benefit of keeping writes in cache, which isn’t Write-Through. And any approach claiming the cache and database are never synchronized contradicts the whole purpose of a cache in this pattern.

Write-Through caching updates both the cache and the backing store (usually a database) at the same time when a write occurs. This means the write is performed synchronously across both places, so the cache and the database stay in sync and subsequent reads can rely on the most up-to-date value being available in the cache. The trade-off is that write latency includes the time to write to both stores, but you gain strong consistency because no stale data can be read from the cache after a write.

Why the other ideas don’t fit: a setup where writes are asynchronous to the database describes Write-Behind, which can lead to temporary inconsistency between cache and storage. A model where only reads are cached loses the benefit of keeping writes in cache, which isn’t Write-Through. And any approach claiming the cache and database are never synchronized contradicts the whole purpose of a cache in this pattern.

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