Sharding is a technique used in database partitioning that separates large databases into smaller, more easily managed parts called data shards. Each shard is held on a separate database server instance to spread the load and improve scalability). Sharding is a form of horizontal scaling or scale-out, as additional nodes are brought on to share the workload.
In sharding, the rows or columns of a larger database table are split into multiple smaller tables, and each new table has the same schema but unique rows. Hashed sharding assigns the shard key to each row of the database by using a mathematical formula called a hash function. The hash function takes the information from the row and produces a hash value, which is used as a shard key to store the information in the corresponding physical shard.
Sharding is useful for organizations that need to store large amounts of data and handle intense workloads. It can improve scalability, increase transaction speed, and reduce downtime by spreading logical shards across multiple servers. However, sharding can also introduce complexity and potential problems, such as premature complexity and increased transaction costs).
Sharding is also used in blockchain to enhance scalability and transaction speed by dividing the network into smaller partitions called shards. Projects like Ethereum, Cardano, and QuarkChain have implemented sharding to address scalability issues. However, sharding in blockchain requires careful implementation due to challenges related to security, complexity, and tight coupling.
