Sharding is a type of database partitioning that separates very large databases into smaller, faster, more easily managed parts called data shards. The word shard means a small part of a whole. Each shard is held on a separate database server instance, to spread load. This allows for databases to be scaled horizontally. Sharding is one of several approaches to database scaling.
History of Sharding
Sharding was first introduced in the early 2000s as a way to scale databases. It was initially used by large companies such as Google and Amazon to manage their large databases. Since then, sharding has become a popular way to scale databases for many different types of applications. It is now used by many companies, including social media platforms, e-commerce sites, and gaming companies.
Comparison of Sharding vs. Other Database Scaling Techniques
|Sharding||Scales horizontally, easy to manage, fast||Requires additional hardware, complex setup|
|Replication||Easy to setup, no additional hardware required||Scales vertically, slower than sharding|
|Caching||Fast, no additional hardware required||Not suitable for large datasets, difficult to manage|
Sharding is a type of database partitioning that separates very large databases into smaller, faster, more easily managed parts called data shards. It is one of several approaches to database scaling and is used by many companies to manage their large databases. Sharding is a fast and efficient way to scale databases, but it requires additional hardware and a complex setup. Other database scaling techniques, such as replication and caching, are also available, but they have their own pros and cons.
For more information about sharding, you can visit the following websites:
- Database Scaling
- Database Partitioning
- Database Clustering
- Database Sharding
- Database Load Balancing
- Database Indexing
- Database Replication
- Database Mirroring