Database clustering definition
Database clustering is a database management technique where multiple database servers are grouped together to work as a single unit (the “cluster”). These servers often have the same hardware and software configurations.
Clustering increases database fault tolerance, reduces downtime, and helps balance server loads. It plays a crucial role in modern database management systems, ensuring that critical applications and users have uninterrupted access to data.
Types of database clustering
- High availability (HA) clustering is focused on providing uninterrupted access to the database. In an HA cluster, multiple nodes operate in parallel, and if one node fails, another takes over seamlessly.
- Load balancing clustering is designed to distribute incoming database queries evenly across the nodes. This improves query response times and prevents overload on any single node.
- Database replication clustering involves copying data from one database node (referred to as the “primary” or “master”) to secondary nodes (known as “replicas”). Database replication clustering is commonly used to offload read-heavy workloads.
- Sharding is a form of clustering where data is partitioned horizontally across multiple nodes. Each shard stores only a subset of the data, allowing the database to handle large datasets and high traffic volumes.