Database Sharding Techniques Guide | Horizontal Partitioning & Scaling

Database sharding is a technique where a large database is partitioned into smaller, more manageable pieces called shards. Each shard contains a subset of the overall data and resides on a separate server.

You should consider sharding when vertical scaling – increasing the resources of a single server – becomes insufficient to handle your growing data volume or query load. Sharding provides horizontal scalability, distributing the workload across multiple machines.

Sharding involves partitioning data across different servers, while replication creates copies of the same data on multiple servers. Sharding focuses on distributing workload, whereas replication ensures high availability and read performance.

Data migration involves moving data between shards during rebalancing, which is the process of redistributing data across different shards. This can be a complex operation that requires careful planning to minimize disruption and performance impact.