Both database partitioning and sharding are techniques used to break down a large database into smaller, more manageable pieces.
However, there are some key differences between the two. they are
- By definition, Database partitioning is the process of dividing a single database into smaller, more manageable pieces, while sharding is the process of horizontally partitioning data across multiple databases.
- In terms of purpose, Database partitioning is primarily used for improving the performance, manageability, and availability of a single database, whereas sharding is primarily used for scaling horizontally across multiple servers or data centers.
- In terms of implementation, Database partitioning is usually implemented at the database level, while sharding is implemented at the application level.
- By granularity, Database partitioning is usually done at the table level or at the index level, while sharding is done at the database or schema level.
- Considering the complexity, Database partitioning is generally less complex than sharding, as it involves only a single database. Sharding, on the other hand, can be complex, as it involves multiple databases that must be managed and coordinated.
In this article, we saw the difference between partitioning and sharding in the database. Database partitioning and sharding are both techniques used to improve the performance and scalability of large databases, but they differ in their approach, purpose, and complexity.