A distributed SQL database consists of several database instances that work together as nodes in a cluster. Each node is a (virtual or physical) server that stores only a subset of the data. Due to the architecture of a cluster, it is easy to add more instances to increase storage capacity and query performance. All copies of the data are synchronized at the same time, which ensures high consistency.
Distributed SQL is designed as a so-called "shared-nothing architecture": The individual nodes work independently of one another and one or more replicas exist for each part ( slice ) of the database in order to achieve the greatest possible redundancy and thus reliability. In such a cluster, the failure of one node has no negative impact on the other nodes or the network. The remaining nodes continue to process all read and write accesses as usual. As soon as the node is available again, the relational database management system automatically ensures that changes to the data are synchronized on all systems.
The system not only balances the data, but also load balances transactions. This means that a single node does not become a bottleneck, resulting in albania telegram screening high performance and high availability. Another key advantage of this architecture is the almost linear horizontal scaling. This means that such clusters are able to process millions of queries per second without compromising data integrity or continuous high availability.
Deploying distributed SQL differs significantly in some respects from working with a conventional client-server RDBMS. The following ten practical tips cover everything from strategic considerations for using distributed SQL to installing MariaDB Xpand and the associated database proxy MaxScale and optimizing the cluster architecture.