What is the difference between sharding and partitioning?

Both terms relate to data partitioning for improved performance and manageability but are used in different contexts.

• Partitioning: Usually applied in the context of individual databases, where a large table is logically divided into smaller, more manageable parts (partitions) based on a certain criterion (e.g., date range, hash). All partitions remain on the same server or database cluster. This improves query performance for data subsets and simplifies administration (backup, recovery).

• Sharding: Used in the context of horizontal scaling of databases, where data is split across multiple independent database instances (shards), which can be located on different servers. Each shard contains a subset of the data and can operate independently. Requests are directed to a specific shard based on shard logic. This allows distributing load and data volume across multiple servers.

Main differences:

Attribute	Partitioning	Sharding
Context	Single database or cluster	Multiple database instances
Physical separation	No (logical within one server)	Yes (across different servers/clusters)
Purpose	Improve manageability and performance within one server	Horizontal scaling, load distribution
Transparency for application	Often transparent to the application	Requires shard logic in the application or proxy
Complexity	Less complex	More complex