Read-Through vs Write-Through Cache
Imagine you’re managing a busy online store. Every time a customer views a product, your system must fetch data quickly to display the page.
To speed things up, you use a cache—a fast, temporary storage that keeps copies of frequently accessed data. But how should you update the cache when data changes?
Two popular strategies are read-through caching and write-through caching.
In this article, we’ll dive into these caching strategies, explain how they work, and discuss their trade-offs.
1. What is Caching?
At its core, caching is about storing frequently accessed data in a fast, temporary storage layer so that future requests can be served quickly without having to hit a slower primary data store (like a database).
Caches are critical in systems design because they:
- Reduce latency: Deliver responses faster by avoiding repetitive, slow database queries.
- Decrease load on databases: Offload repetitive read or write operations.
- Improve scalability: Allow systems to handle more traffic with less strain on backend systems.
However, keeping the cache in sync with the primary data store is essential, and that’s where caching strategies come into play.