Database Scaling: Sharding and Replication
Database Scaling: Sharding and Replication Scaling a database means handling more users, more data, and faster queries without slowing down the service. Two common methods help achieve this: sharding and replication. They answer different questions—how data is stored and how it is served. Sharding splits the data across multiple machines. Each shard holds a subset of the data, so writes and reads can run in parallel. Common strategies are hash-based sharding, where a key like user_id determines the shard, and range-based sharding, where data is placed by a value interval. Pros: higher write throughput and easier capacity growth. Cons: cross-shard queries become harder, and rebalancing requires care. A practical tip is to choose a shard key that distributes evenly and to plan automatic splitting when a shard grows. ...