In today's fast-paced world of software development, microservices have become a popular way to build applications. They provide great scalability, flexibility, and agility. However, keeping these microservices systems running efficiently can be challenging as they become more complex and larger. This is where caching comes in as an important strategy to boost the performance of microservices.

If you're a backend developer, caching is a great way to speed up your web application. However, many details about caching are often overlooked when picking the best caching strategy for your app. This article will explore the different caching strategies available and how to choose the right one for your specific needs.

What is Caching?

It is the procedure of putting data into memory and retrieving it (i.e. cache memory). Caching's primary function is to shorten the time it takes to retrieve particular data. The goal of caching is to save information that may come into use later. Caching is necessary since it takes a long time to retrieve data from permanent memory, which includes hard drives like HDDs and SDDs, slowing down the process. Caching therefore shortens the time needed to retrieve the data from memory. To minimize the necessity for accessing the data storage layer, cache memory—a high-speed data storage layer—is utilized to store data. Fast access hardware is used to implement cache memory (RAM).

Caching allows you to reuse data that has already been processed. When hardware or software requests specific data, it first looks in the cache memory. If the data is found there, it’s called a cache hit. If the data isn't found, it's called a cache miss.

Why is Caching Important?  

• It is essential for enhancing system performance.
• It decreases overall time and increases system efficiency.
• Caching is essential because it delivers high performance in computer technology.
• It typically doesn't generate new requests.
• It prevents the need to reprocess data.

Top 5 Server Caching Techniques for Enhanced Performance of Your Application

Cache Aside 

In this caching strategy, the cache is separate. The application looks for the requested information in either the database or the cache. Initially, it checks the cache; if the data is found, it's known as a cache hit, and the application reads and returns this data. If the data isn’t found, it results in a cache miss. In this case, the app queries the database for information. Then, it delivers the data to the client. This process lets the app store data in the cache for future use. It is crucial to collaborate with the best mobile app development company in the USA.

In read-heavy use situations, it is essentially helpful. Therefore, if the cache server is unavailable, the system will continue to function by establishing direct contact with the database; however, this is not a permanent or reliable solution in the event of peak load or unexpected surges.

Directly writing to the database is the most popular writing technique; however, doing this too often could result in inconsistent data. Developers frequently employ a cache with a Time to Live (TTL) to handle this scenario and keep serving until it expires.  

Write-Through Cache

As the name implies, this technique writes any new data into the cache before the main memory or database. The cache in this instance is logically situated between the database and the application. As a result, if a client requests any information, the information is directly obtained from the cache and provided to the client, saving the application the trouble of first checking with the cache to see if it is available. Nevertheless, it causes a write operation's latency to increase. However, we can guarantee data consistency if the read-through cache is combined with another caching technique.

Read-Through Cache 

With this caching technique, the cache and database are positioned so that if a cache miss occurs—when data is not found in the cache—the missing data is filled in from the database and sent back to the client.

It is most effective in ready-heavy applications where the same data set is repeatedly requested, as you would have anticipated. For example, a news website would repeatedly present the same stories for a whole day.

This strategy's drawback is that it will always result in a cache miss when requesting data for the first time, making it slower than a regular request.

Write-Back

Under this caching approach, when a write operation occurs, the app writes the data to the cache. The cache immediately recognizes the changes. A little while later, the cache returns the data to the database. Another name for it is the Write-behind caching approach.

This caching technique boosts write performance for write-heavy apps. Additionally, it can aid in accommodating occasional, mild database failures and outages.

It can also function effectively in conjunction with a read-through cache. If batching is supported, it can also lessen the write stress on the database. The drawback is that the data may be permanently lost during a cache failure. In most relational databases, the write-back caching method is enabled by default.

Write-Around

When data is written once and read only a few times, it can be used in conjunction with the read-through cache and may be a wise option. For instance, in situations when real-time discussions or logs are required.

Conclusion 

In this article, we covered what caching is, the top 5 techniques for enhanced application performance, and why it's necessary. Then, we also reviewed various caching algorithms for server-side caching. It is generally advised to combine these caching algorithms for optimal results. At the same time, no one of them needs to satisfy your practical use cases.

To develop the ideal solution for a use case, a novice developer may need to experiment a bit. This will help them gain a practical understanding of the idea.