Data Replication Models

Replication models

With the increase in data volumes, it becomes difficult and unviable to scale up database servers- buy a bigger server to run the database on. Another suitable strategy is to distribute the data among a number of servers. With this strategy, aggregate orientation fits well because it is a natural unit used for distribution.

There are various distribution models based on handling a larger quantity of data, high throughput, and availability during planned and unplanned events. Along with these benefits, distributing data across multiple servers brings complexity incurring costs to the system.

Mainly, there are two techniques for data distribution: replication and sharding. Both techniques are orthogonal to each other in the sense that replication copies data across multiple servers while sharding puts different data on different servers. One can use either or both of them. The following sections discuss single server, primary-secondary and peer-to-peer replication, while data sharding is discussed in forthcoming lessons.