Read-Through
In the Read-Through caching approach, the cache is positioned between the application and the database. Whenever the data requests come, the application goes to the cache first. If the requested data is found, simply return it. Otherwise, the cache fetches the data from the database and then returns it to the application. The cache is responsible for fetching data from the database. It is suitable for applications with read-heavy workload .
Example: A Read-Through strategy is preferable for social media platforms.
The below image shows the Read-Through strategy working mechanism. Assume a social media platform,
- When a user login the application, request the user profile details from the cache.
- If profile details exist, return it.
- Otherwise, Cache is responsible for fetching user profile details from the DB and storing it in the cache then returning the response to the application.
What is Caching Strategies in DBMS?
In today’s digital world, the speed of an application plays a major role in its success. Generally, users expect the applications to run faster with quick responses. Also, It should support seamless experiences across all their digital interactions, whether they’re browsing a website, mobile app, or a software platform. Caching is used to implement a high-speed system with a large number of users. A cache is a high-speed data storage that stores data temporarily to serve future requests faster.
Database caching is like a helper for your primary database (DB). It is a mechanism that stores frequently accessed data in temporary memory. Whenever the application requests the data again, that can quickly get it from this helper, instead of from the main database. Cache helps to reduce the database workloads. So it increases system speed by reducing the need to fetch data from DB.