Database Sharding
allows horizontal scaling
Sharding involves separating different rows of information from the table and storing them on different machines.
Sharding disperses data across various databases or servers, while partitioning segregates data within a single database instance into subsets.
- Partitioning is used to improve data management and performance optimization within a database.
Resources
Why sharding?
Database sharding is needed to address scalability, performance, and availability challenges in large-scale systems/
As the size of a database grows, so does the time it takes to perform certain operations (e.g., indexing, querying, and updating records). Additionally, a single database server may struggle to handle a large volume of concurrent read and write operations.