Database Caching: Everything You Should Know

What is Database Caching and what are its popular strategies? Today we’ll answer this question in detail. It’s a fact that data store technology is used in databases. You might have heard of database cache and wondered what it might mean. It uses this same data store technology. Your database needs to help in data retrieval that plays a key role in boosting your commercial applications’ user experience with success.

What does database caching mean and why it is so important?

Database caching refers to a buffering technique were frequently queried data is stored in temporary memory space. It makes this data simple for the user to access and reduces the workload for the database.

For instance, if you need to retrieve any user profile from your database, you need to move from one server to another server.

After you have searched for the user for the first time, the profile is stored in a space that is located close to you on the database. This reduces the time you need to search for the user profile when you need to access it again.

This database cache can be created on different tiers or exist on its own. This relies on the instances of use. The cache works with every kind of database and includes relational databases and No SQL databases.

What are the advantages of database caching?

1. Performance – The database’s performance is boosted as it makes data simple to be accessed via the cache and decreases the workloads for the database.

2. Scalability – The workload of backend queries is distributed to the database cache that reduces costs, and permits for more flexibility in the data processing.

3. Availability – If the backend server is not available; the database cache can offer ongoing service to the app, making the database system resilient to any failures.

On the whole, database caching refers to an invasive strategy that is minimal to boost the application’s performance by incorporating caching with the extra advantages of availability and scalability.

What are the popular strategies for database caching?

Qualified and trained professionals in database administration and management recommend you have a database caching strategy for determining the relationship between the caching system and data source and how your data can be accessed. There are multiple strategies for you to implement cache, and every one of them will have a unique impact on the system design and its resulted performance.

DBA specialists from the esteemed company, RemoteDBA.com, say that before you design the architecture, it is beneficial to know how your data needed to be accessed so that you can choose the strategy that is best suited to it.

Given below are some of the popular strategies for database caching:

1. Cache Aside – In this particular strategy, the cache sits aside your database. The application at first requests data from the cache, and if it is present there (known as a cache hit), the application retrieves this data directly.

If the data is not present (otherwise known as a cache miss), the application will request this data from the database system and write it inside the cache so that the next time you search for this data, it can be quickly retrieved from the cache again.

2. Read Through – Contrary to the above, this cache sits between the database and the application. The application requests the data from the cache. In the event of a cache miss, it is responsible for getting the requested data from the database, update it, and return it to the application.

3. Write through – This strategy is similar to the write-through strategy with the cache between the database and the application. Every write is taken from the application and goes through the database cache.

4. Write back (also known as write-behind) – This strategy is more or less the same as write through. The application still writes data to the cache. However, there is a delay in this writing from the cache to your database. The cache flushes out updated data to the database frequently, for instance, every two minutes.

5. Write Around – The write around strategy generally combines with tother the read through or the cache aside strategy. This application will directly write to the database, and the data that is read goes to the cache.

Experienced database administrators and consultants recommend that is practice. You should know which strategy to deploy for your system.

The following is a table that summarizes the advantages and the disadvantages of each:

Strategy	Advantages	Disadvantages
Cache aside	Resilient to failures when the database suffers from downtime Simple to implement The data model might not be the same between the database and cache Perfect for read-heavy database workloads in general	Inconsistency in data might take place between database and cache Will always result in a cache miss the first-time and boost latency
Read Through	The code is more readable as the application is not sure about the database. Ideal for database read-heavy workloads when the same set of data is frequently requested	There is a need to write a complex plug-in for the cache to get data for the first time It Will always result in a cache miss for the first time to boost latency
Write Through	The data is available always in the cache and does not result in a cache miss The consistency of data is guaranteed when paired with the read-through strategy	Increases write latency
Write Back	Ideal for write-heavy workloads Is resilient to database failure moderate in nature Reduces the costs and workload by reducing writes to the database	In the event of a cache failure, permanent loss of data will occur

Experts in database administration and management suggest that before choosing the best database caching technique and strategy; make sure you compare them with their pros and cons. In this way, you can get the best database caching strategy for your commercial needs and boost your customers’ user experience with success!

Did I miss something? If you’re an expert on database caching and want to share your thoughts, please comment below.

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