Here, we will discuss concepts related to database sharding, the benefits and drawbacks of sharding, and its architecture of sharding. In the modern age of technology, each data is stored within an organization related to their products, sales, and marketing to analyze the performance analysis of the organization. The data decisions are made through insights reports of performance analysis. Since data keeps on growing day by day, a solution needs to be found out to scale the database, its performance falls down and load increases.
To store such huge datasets, a new concept has evolved that is called sharding. Let’s quickly discuss each section in a detailed way as follows.
Database Sharding is the breaking down of multiple tables into various smaller chunks or tables, which is called shards. Sharding also distributes the data across several multiple clusters or machines. The data which is stored in each shard is independent and different from other shards. It is almost similar to scale the database horizontally, which is also called horizontal partitioning.
Now let’s quickly understand the different architectures of Database Sharding. Various types of Database Sharding Architectures can be chosen depending on your requirements as follows:
Database Sharding can be a great solution for customers looking to scale their database horizontally and vertically. However, it also adds complexity as well as a point of failure to the application. Sharding may be important for some, but the time and resources for creating and maintaining architecture could outperform the benefits for others.
In this article, you must have got a clear idea about the pros and cons of Sharding. Also, you can get the insight to make a more informed decision whether or not the Sharded database architecture is best suited for your application.
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