Common Cache Read/Write Strategies for Production Environments

After a series of introductory articles on Redis fundamentals, this article examines how Redis is used as a cache together with relational databases such as MySQL in production.

It first describes the simple write‑DB‑then‑cache / read‑cache‑then‑DB strategy, explains its advantages (simplicity, no extra components) and disadvantages (stale reads under concurrent updates).

Next, the Cache‑Aside (cache‑bypass) pattern is presented, detailing its read flow (cache → DB → cache) and write flow (DB update then cache eviction), along with its pros (simplicity, better consistency) and cons (potential cache‑miss overhead).

The article then introduces the Write/Read‑Through pattern, which relies on a third‑party cache‑synchronization component, outlines its read and write processes, and discusses its benefits (most operations hit cache) and drawbacks (added latency on cache‑miss writes and increased system complexity).

Write‑Back is briefly covered as an OS‑style caching method, describing its dirty‑data handling for reads and writes, and noting that it is complex and rarely used in production.

Additional common techniques such as LRU eviction for hot keys are mentioned, emphasizing that only frequently accessed data should be cached in large‑scale scenarios.

In summary, five cache read/write strategies are compared, and readers are encouraged to choose and adapt the one that best fits their business requirements.