Sharded is an adjective used to describe a distributed database or system architecture that employs a technique called sharding. Sharding refers to the process of horizontally partitioning a large database or system into smaller, more manageable pieces referred to as shards. Each shard contains a subset of the data or workload, and together, they form the complete database or system.
The purpose of sharding is to distribute the data and workload across multiple machines or servers, in order to improve performance, scalability and availability. By dividing the data into smaller chunks, each shard can be stored on a separate server, allowing for parallel processing and reducing the load on individual nodes. This can result in faster query response times and higher throughput.
When a database or system is sharded, each shard operates independently and may even be located on different servers or data centers. However, sharded architectures typically include mechanisms for coordinating and managing the shards, ensuring data consistency, and routing queries to the appropriate shard.
Sharding is often used in large-scale applications, where handling significant amounts of data or heavy workloads is necessary. It is commonly employed in distributed databases, such as NoSQL databases, as well as in web applications, cloud computing, and other distributed systems.
