How does database sharding work?

Sharding is a technique used to scale out relational databases by storing partitions of data across multiple servers instead of putting everything on a single server. This allows for more efficient use of resources and improved scalability. Sharding can be done at different levels, such as row-level (horizontal) or schema-level (vertical), and involves deciding how to split up data into shards based on the business model and query load. The process of sharding includes planning and executing a migration, building a routing layer to direct queries to the correct databases, and managing hotspots where servers become overloaded with data. While some teams build their own sharding solutions from scratch, there are also tools and frameworks available, such as Vitess for MySQL and Citus for Postgres, that can simplify the process. The trend of using "serverless" databases, which automatically handle sharding and scaling, is gaining traction, offering an alternative to traditional sharding approaches.

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