How Distributed SQL on PostgreSQL help you in building WebScale Database Infrastructure for Performance, Scalability and Reliability

Distributed SQL is a method of horizontally scaling a SQL database by distributing the data and query processing across multiple machines. In PostgreSQL, this can be achieved using techniques such as sharding, which divides the data into smaller chunks and stores them on different machines, and replication, which creates multiple copies of the data across different machines.

By distributing the data and query processing across multiple machines, distributed SQL can help to improve the performance and scalability of PostgreSQL. For example, by splitting the data into smaller chunks, it can reduce the amount of data that needs to be read or written by a single query, thus improving query performance. Additionally, by having multiple copies of the data, it can help to ensure high availability and fault tolerance in the event of a machine failure.

Furthermore, distributed SQL also helps in terms of reliability. With a single point of failure, the entire system can crash. However, with a distributed SQL, the data is replicated across multiple servers, which means that if one server fails, the data is still available on other servers.

In summary, Distributed SQL helps PostgreSQL in horizontal scalability, performance and reliability by distributing data and query processing across multiple machines, reducing the amount of data that needs to be read or written by a single query, ensuring high availability and fault tolerance, and providing data replication across multiple servers.