Sharding is a database architecture technique used to improve performance, manageability, and scalability of large-scale databases. In a sharded system, the data is partitioned into smaller, more manageable pieces called "shards," each of which can be stored on a separate server. This allows for horizontal scaling, as adding more shards essentially adds more resources to handle increased loads. Sharding is particularly useful for distributed databases and is commonly employed in systems that require high availability and low latency, such as e-commerce platforms, social media sites, and real-time analytics applications. The strategy for how to divide the data—whether it's based on range, hash, or directory-based sharding—varies depending on the specific needs of the application. Overall, sharding is a crucial concept for efficiently managing large datasets in a distributed environment.