Sharding is a database partitioning technique that splits large datasets into smaller, manageable pieces called "shards." Each shard contains a subset of the data, stored across multiple servers or nodes, improving scalability and performance. By distributing data, sharding reduces the load on individual servers, enabling faster query processing and handling larger volumes of traffic. It’s widely used in distributed systems like blockchain, NoSQL databases (e.g., MongoDB, Cassandra), and big data applications. Sharding can be horizontal (splitting rows across shards) or vertical (splitting columns). While it enhances efficiency, it introduces challenges like data consistency, complex queries across shards, and rebalancing when adding nodes. Properly implemented, sharding optimizes resource use and supports massive, high-throughput systems.