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.
Why is Database Caching Strategy Important?
- Improved System Performance: In general, the frequently used data is stored in the cache. So the applications can retrieve that data more quickly from the cache instead of the primary DB. It improves the system performance and reduces latency.
- Increase Data Availability: Caching increases data availability if the primary DB goes down, caching acts as a backup source. Depending on where the cache is stored, it can still serve data to the application even if the primary DB is unavailable.
- Cost Savings: The caching mechanism reduces DB server load. Caching can help to build the infrastructure with lower costs compared to DB servers. It allows organizations to achieve the same level of performance with fewer resources.
- Improved User Experience: Using the Caching technique responses are returned faster. It leads to a better overall user experience, particularly for applications that require real-time or near-real-time access to data.
Caching Strategies
There are five major caching strategies.
- Cache-Aside
- Read-Through
- Write-Through
- Write-Back
- Write-Around
Cache-Aside
In the Cache-Aside caching strategy, the cache is resided next to the database. Here the application is responsible for managing the cache. Whenever the data requests come, the application checks the cache at first. If the asked data is available in the cache, simply return it. Otherwise, data is retrieved from the database and stored in the cache for future usage. It is also called Lazy Loading.
Example: Cache-Aside strategy is suitable for e-commerce websites.
The below image shows the Cache-Aside strategy working mechanism. Consider an e-commerce web application with a large amount of customers.
- Generally, the e-commerce application requests product details (name, price) more often.
- Using cache-aside, whenever a customer requests a product page, the application first checks the cache whether it contains product details or not.
- If the data exists, return the product details from the cache. Otherwise, fetch the product details from the database and store them in the cache.
Cache-Aside Strategy
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.
Read-Through Strategy
Write-Through
In the Write-Through cache mechanism, the application writes data to the cache and the database simultaneously. Whenever the data is added or updated, that is written to the cache and the database at the time. Also, it reduces read delays, because data is directly fetched from the cache. However, it slows down write operations because of double the time write operation.
Example: A Write-Through strategy is suggested for banking applications.
The below image shows the Write-Through strategy working mechanism. Let’s say a banking application, the users frequently perform transactions like deposits and withdrawals.
- For each transaction application needs to update the user’s account balance. So the application writes user account balance details in the cache and cache writes the balance info to the DB immediately.
- Write-through caching provides consistency between the cache and database. So that users always receive reliable information about their account balances.
Write-Through Strategy
Write-Back
In a Write-Back strategy, the application directly writes the data to the cache at first, then after some delay data is written to the database. It ensures recent data is always present in the cache. So the data is easily accessible. This method is suitable for applications with a write-heavy workload. There is possible to risk of data loss if the cache fails before writing to the database. If the cache is not handled properly, it will lead to data inconsistency between the cache and the database. It is also called Write-Behind.
Example: The Write-Back strategy is suitable for the Content Management System (CMS).
The below image shows the Write-Through strategy working mechanism. Consider a content management system that is used for blogging. Authors frequently add or update their blog posts.
- The application first writes the content changes to the cache. Then the cache does write operation to the database with delay (for a predefined period).
- During this delay period, if the author makes further updates to the same blog post, the changes are overwritten by updated content on the cache.
Write-Back Strategy
Write-Around
Generally, a Write-Around mechanism combines with a Read-Through caching approach or Cache-Aside strategy. The application always writes the data into the database and reads data from the cache. If there’s a cache miss, the data is fetched from the database and then stored in the cache for future reads. This strategy works best when data is rarely updated and read in more often.
Example: Write-Around strategy is suggested for Cloud Storage Service.
The below image shows the Write-Around strategy working mechanism. Consider a cloud storage service where users frequently upload large files like videos and images.
- Whenever the users newly upload files, the system uses a write-around caching strategy to store them on the backend storage without caching them.
- Similarly, if a user requests to access a file, the system checks the cache first. If the file is found in the cache return it directly. Otherwise fetch the file from the backend storage and return it to the user.
Write-Around Strategy
Comparative Analysis of Caching Strategies
|
Caching Strategies |
Advantages |
Disadvantages |
|---|---|---|
|
Cache-Aside |
This approach is efficient for read-heavy workload applications. It allows flexibility in data models compared to the database. |
Risk of inconsistency between the cache and database. Data written directly to the database may not immediately reflect in the cache, leading to potential inconsistencies. |
|
Read-Through |
It simplifies the application logic because the cache handles data retrieval. It is also suitable for read-heavy workload applications. |
This approach increases the database load. For every new data request, results are returned from the database instead of the cache. Maintaining the data consistency between the cache and database is complex. |
|
Write-Through |
Write-through caching ensures data consistency between the cache and database. It supports faster write operations. |
This method requires more time for write operations because data should be written in the both cache and the database. Write-through caching is complex because it requires careful coordination between the cache and the database. |
|
Write-Back |
This caching can improve overall write performance because it reduces the number of write operations to the database. It is suitable for applications with a write-heavy workload. |
There’s a risk of data loss if the cache fails before writing to the database. While using the Write-back method, there can be data inconsistency occurs between the cache and the database |
|
Write-Around |
This caching strategy is mainly used to improve the application and database performance. It prevents cache pollution. Because it efficiently handles the cache. |
This method increases the read latency if the cache miss. There is a possible risk of returning outdated information. |
Conclusion
In general, implementing an appropriate caching strategy will definitely lead to improved overall system performance. Also, it helps to increase the data availability, and user experience and optimize resource utilization, reducing the time delay, especially for applications with large database workloads. Overall, The applications can choose the caching strategy based on their requirements.
Frequently Asked Questions on Database Caching Strategy – FAQs
What is database caching?
Database caching 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.
Which is the most commonly used caching mechanism?
The Cache-Aside strategy is the most commonly used caching mechanism. Generally, it is used in e-commerce and other web applications. It is also called Lazy Loading.
Which caching strategy is suitable for applications with frequent read operations?
A Read-Through caching strategy is suitable for applications with frequent read operations. Read-Through caching involves fetching data from the main DB through the cache.
Which caching strategy ensure the data consistency between the cache and DB?
A Write-Through caching strategy ensures data consistency between the cache and DB. So it is used in the banking application which contains reliable information.
Which caching strategy is suitable for blogging applications?
The Write-Back caching strategy is suitable for blogging applications. The application first writes the content changes to the cache. Then the cache does write operation to the database with delay.
Which caching strategy may lead to data loss?
The Write-Back caching strategy may lead to data loss. Because the application directly writes the data to the cache at first, then the cache writes to the DB after some delay. There is a possible risk of data loss if the cache fails before writing to the database.