How is data sharding implemented in a database?

Data sharding is a method of horizontal scaling of a database, where data is partitioned into parts (shards), each stored separately.

Main sharding methods:

• Range-based sharding: data is distributed across ranges of keys, for example, users with IDs from 1 to 1000 in one shard, from 1001 to 2000 in another.
• Hash-based sharding: keys are processed through a hash function, whose result determines the shard where data will go. This ensures even distribution.
• Geographical sharding: user data from different regions is stored in corresponding shards.

In applications, routing logic is usually implemented to direct requests to the correct shard, ensuring proper data access.