Sharding is a technique used in database systems to partition data across multiple servers. This allows for better performance and increased scalability as the load is distributed among different shards or partitions instead of relying on a single server.
In order to implement sharding, the database is first partitioned into smaller subsets of data. Each of these subsets is then assigned to a different server or shard. When a query is executed, the system determines which shard contains the relevant data and executes the query on that shard. The results from each shard are then combined and returned to the user as if they were obtained from a single database.
Sharding offers several benefits, including improved query performance, increased availability and reliability, and the ability to handle large amounts of data without degradation in performance. However, it also comes with some challenges, such as the need for careful partitioning and balancing of data across shards, and the potential for data inconsistency if different shards are out of sync.
