In read-through caching, what role does the cache play?

In read-through caching, what role does the cache play?

• A. The cache writes data back to the database on every update.
• B. The cache acts as a proxy between the application and the database, fetching data on cache misses automatically.
• C. The cache is a simple in-process store used only for feature flags.
• D. The cache uses TTL to expire all items immediately.

Answer: (B)

Read-through caching places the cache between the application and the database, so it automatically handles data retrieval for you. When the application requests data, the cache first checks if it’s already stored. If it is, the data is returned quickly from the cache. If not, the cache fetches the data from the database, stores it in the cache, and then returns it to the application. This automatic fetch on cache misses is what makes read-through caching efficient: it shields the application from having to know where data lives and reduces database load by serving popular reads from the cache. The other scenarios describe different patterns or limitations. Writing data back to the database on every update aligns with a write-through/write-behind pattern, not the read-through flow. Treating the cache as a simple in-process store for feature flags narrows its role and overlooks the general caching layer used for data reads. Expiring all items immediately with TTL would negate the benefit of caching, since TTL governs expiration over time, not an immediate blanket purge.

Read-through caching places the cache between the application and the database, so it automatically handles data retrieval for you. When the application requests data, the cache first checks if it’s already stored. If it is, the data is returned quickly from the cache. If not, the cache fetches the data from the database, stores it in the cache, and then returns it to the application. This automatic fetch on cache misses is what makes read-through caching efficient: it shields the application from having to know where data lives and reduces database load by serving popular reads from the cache.

The other scenarios describe different patterns or limitations. Writing data back to the database on every update aligns with a write-through/write-behind pattern, not the read-through flow. Treating the cache as a simple in-process store for feature flags narrows its role and overlooks the general caching layer used for data reads. Expiring all items immediately with TTL would negate the benefit of caching, since TTL governs expiration over time, not an immediate blanket purge.