What is database caching? Defining the best caching strategy for your app

Database caching is an important way to help improve the speed of your applications. This article will explain strategies for best using this method to improve database performance.

Defining database caching

Caching is a data storage process that plays an essential role in designing scalable applications. A cache is any data store that can hold and retrieve data quickly for future use. This enables faster response times and decreases the load on the system. Database caching is a process that is implemented by keeping frequently accessed data in a separate data store so that the subsequent requests for the same data will be faster. This will do the following:

  • Improve the server response times and system performance.
  • Minimize latency and overhead associated with querying data by reducing the need to fetch it from the database.
  • Take advantage of the locality principle, meaning storing data closer to where it’s needed. It also involves storing precomputed data that would otherwise be difficult to serve on demand. Without database caching, applications would run more slowly, due to the access time of retrieving data.

Caching strategies and their purpose

Database caching strategies can help improve the performance and efficiency of accessing data from a database by leveraging the use of caches. The caching strategies can do more than traditional database access to achieve greater performance. Reasons to implement caching strategies Implementing caching strategies in an application brings several benefits and advantages:

  1. Improved performance: Caching enhances application performance by reducing data retrieval time and providing faster response times. In the application, faster response times enhance the user experience.
  2. Reduced database load: Caching can reduce the number of database queries on the database server, thus reducing the load on it.
  3. Cost efficiency: Caching can reduce the cost of running an application by optimizing resource utilization and reducing expensive database and infrastructure requirements.
  4. Scalability and availability: Caching improves application scalability and availability by distributing the workload and ensuring high data availability.

List of caching strategies

The relationship between the database and cache can significantly influence system performance. Hence, it is very important to choose the best caching strategy before implementing database caching. Let's have a look at the common caching strategies. The common caching strategies used in database systems are:

  • Cache-aside caching.
  • Read-through caching.
  • Write-back (write-behind) caching.
  • Write-through caching.
  • Write-around caching.

Cache-aside caching

Cache-aside caching strategy involves the application being responsible for reading or writing data to the cache. When some data is required in the application, it first queries the cache. If the data is present in the cache, it will be retrieved. If the data is not present there, the application will fetch the data from the database. Then this data will be stored in the cache, before returning it to the requester. Cache Diagram

Read-through caching

In read-through caching, the cache will sit between the application and the database. The application will look for the data in the cache initially. If the data is not present in the cache, the application will then query the database. The retrieved data will then be stored in the cache by the database (hydrate), which returns it to the application. Read-Through Caching Diagram

This caching strategy will improve performance and latency by optimizing read operations, thereby reducing the need of accessing the database. Read-through caching is most effective in applications where the read-to-write ratio is high, meaning there are more read operations, compared to write operations, and for applications where data doesn't change frequently.

Write-back caching

Write-back caching or write-behind caching involves the application writing data to the cache, and the cache updating the data asynchronously. When a write operation occurs, the data will be written to the cache. The cache will update the database at a later time selected, based on various criteria like memory or flush capacity. Write-Back Caching Diagram

This strategy enables write operations to be completed faster since the data is initially stored in the cache. The cache typically has lower latency and higher throughput than the persistent storage like a database. The writing of data from the cache to the database can be optimized by batching multiple writes together and performing them asynchronously in the background. One disadvantage of this strategy is that it introduces the risk of potential data loss if the cache fails before writing into the database. To mitigate this risk, the caching system implements mechanisms like write-acknowledgments and periodic flushing of cached data to the database.

Write-through caching

Write-through caching involves the application writing data both to the cache and the database simultaneously. Write-Through Caching Diagram This strategy ensures that both the cache and database remain consistent and data is always up-to-date and available in both locations. It also improves write performance, since writes are initially made to the cache. Thus this approach is particularly useful in scenarios that are write-heavy or write-to-read ratio is relatively balanced. A disadvantage of this strategy is that it may introduce additional overhead due to the extra write operations.

Write-around caching

Write-around caching involves the data being written initially to the underlying database directly instead of the cache. In this approach, the cache will only be updated when the data is read from it. Write-Around Caching

The most important advantage of this approach is that it gives priority to the write operations, assuming they are infrequent and have less importance on the read operations. This makes it useful for write-intensive workloads or for data that is not frequently accessed. By bypassing the cache, write-around caching reduces cache pollution (cache filled with data that is not frequently accessed or not relevant). Some of the disadvantages of this approach include increased read latency for newly written data since data needs to be fetched from the database. Another disadvantage is the temporary inconsistency that can happen between the cache and the data source.


In this article, we have gone through the concept of database caching and various caching strategies. By the implementation of caching strategies, your application can utilize the full potential of databases. There are many caching solutions available now. However, not all applications will have the same caching strategies, and it is important to choose the right caching strategies based on the requirements and nature of your application.

PlanetScale Boost is a caching solution that can make your application’s queries up to 1,000× faster queries in just a few clicks with our groundbreaking caching technology. Get started with PlanetScale Boost.

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