Sharding is a database design technique that is used to improve the performance and scalability of a database. In a sharded database, the data is divided into smaller pieces, called shards, which are stored on different servers or machines. This allows the database to distribute the workload across multiple servers, which can improve performance and make the database more scalable.
One of the main benefits of Sharding is that it allows a database to handle more data and more concurrent users without sacrificing performance. In a non-sharded database, the amount of data and the number of users that the database can handle is limited by the capabilities of the server on which the database is running. In a sharded database, the data and the workload are distributed across multiple servers, so the database can handle more data and more users without running into performance issues.
Another benefit of Sharding is that it can improve the availability and reliability of a database. In a non-sharded database, a single server failure can cause the entire database to go down. In a sharded database, each shard is stored on a separate server, so a failure on one server will not affect the other shards. This can improve the overall availability and reliability of the database.
Sharding is used in many different types of databases, including relational databases, NoSQL databases, and distributed databases. It is particularly useful in situations where a database needs to handle a large amount of data or a high number of concurrent users, and where the performance and scalability of the database are critical.
Overall, Sharding is a valuable technique for improving the performance and scalability of a database. By dividing the data and the workload across multiple servers, a sharded database can handle more data and more users without sacrificing performance, and can also improve the availability and reliability of the database.