Cache Strategies

My previous post on System Design Concepts mentioned caching strategies. In this post, I will focus on the motivation behind the differences between those strategies and how performance is affected.

Why Are There Different Caching Strategies?

Different caching strategies exist because only some approaches can address the diverse requirements of all applications. The choice of strategy depends on factors like data access patterns, consistency requirements, latency tolerance, and the nature of read and write operations.

Strong Consistency vs. Performance

Some applications, like financial systems, prioritize consistency over performance, making strategies like write-through more suitable. Conversely, applications requiring high performance but tolerating minor inconsistencies might benefit from write-back caching.

Write-through is commonly used for scenarios like real-time stock updates in e-commerce, where data is written to the cache and database to ensure strong consistency despite the higher cost.

Read-Heavy vs. Write-Heavy Workloads:

Systems with predominantly read operations may rely on read-through or cache-aside strategies. Write-heavy systems may choose write-around or write-back strategies to reduce cache pressure. Popular news on websites is often cached to reduce latency and optimize performance.

Data Freshness