Overview
Both are strategies for keeping a cache (often Redis) in front of a database, and they differ in when the cache gets populated. With cache-aside (lazy loading), the application checks the cache, and on a miss reads the database and stores the result — only requested data is cached, but the first read after a miss or expiry is slow. With write-through, every write updates the cache and the database synchronously, so reads are always fast and never stale, at the cost of slower writes and caching data that may never be read.
Cache-Aside vs Write-Through: key differences
| Cache-Aside | Write-Through | |
|---|---|---|
| Cache filled | On read miss (lazy) | On every write (eager) |
| Read after miss | Slow (hits the DB) | Always fast (already cached) |
| Write latency | Low (DB only) | Higher (DB + cache) |
| Staleness risk | Until TTL/invalidation | Low — cache tracks writes |
| Wasted cache | None (only read data) | Possible (writes never read back) |
When to use Cache-Aside
General-purpose caching where read patterns are unpredictable and you want the cache to hold only what is actually requested; the most common default.
When to use Write-Through
Read-heavy data that is also written often and must always be served fast and fresh, where the extra write cost and possible wasted cache are acceptable.
Verdict
Cache-aside is the pragmatic default — simple, memory-efficient, and resilient (a cache outage just means slower reads). Add write-through (often alongside read-through) when you can't tolerate the post-expiry slow read and the data is hot enough to justify caching on write. Watch for cache stampedes with cache-aside on popular keys.
Common questions
What is the difference between cache-aside and write-through?
Cache-aside populates the cache lazily on a read miss; write-through populates it eagerly on every write. Cache-aside is simpler and memory-efficient; write-through keeps reads fast and fresh at the cost of slower writes.
Which caching strategy is most common?
Cache-aside (lazy loading) is the most widely used because it is simple, only caches data that is actually read, and degrades gracefully if the cache fails.