Sharding is a very important concept which helps the system to keep data into different resources according to the sharding process.
The word “Shard” means “a small part of a whole“. Hence Sharding means dividing a larger part into smaller parts.
In DBMS, Sharding is a type of DataBase partitioning in which a large DataBase is divided or partitioned into smaller data, also known as shards. These shards are not only smaller, but also faster and hence easily manageable.
Need for Sharding:
Consider a very large database whose sharding has not been done. For example, let’s take a DataBase of a college in which all the student’s record (present and past) in the whole college are maintained in a single database. So, it would contain very very large number of data, say 100, 000 records.
Now when we need to find a student from this Database, each time around 100, 000 transactions has to be done to find the student, which is very very costly.
Now consider the same college students records, divided into smaller data shards based on years. Now each data shard will have around 1000-5000 students records only. So not only the database became much more manageable, but also the transaction cost of each time also reduces by a huge factor, which is achieved by Sharding.
Hence this is why Sharding is needed.
Features of Sharding:
- Sharding makes the Database smaller
- Sharding makes the Database faster
- Sharding makes the Database much more easily manageable
- Sharding can be a complex operation sometimes
- Sharding reduces the transaction cost of the Database
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