Getting Started with IntelliJ IDEA and Distributed SQL - The Distributed SQL Blog

Getting Started with IntelliJ IDEA and Distributed SQL - The Distributed SQL Blog

Because YugabyteDB is PostgreSQL compatible, it works with IntelliJ IDEA out of the box. See how to test out basic IntelliJ features with YugabyteDB distributed SQL database.

IntelliJ IDEA is a popular integrated development environment (IDE) written in Java for developing software. It is developed by JetBrains and is available as an Apache 2 licensed community edition and in a proprietary commercial edition. IntelliJ supports a variety of datasources within their IDE. Because YugabyteDB is PostgreSQL compatible, most third-party tools and apps will work “out of the box.” IntelliJ is no exception here.

In this blog post we’ll walk you though the following steps:

  • Install a 3 node YugabyteDB cluster on Google Kubernetes Platform
  • Install the Northwind sample database
  • Configure IntelliJ to work with YugabyteDB
  • Test out some basic IntelliJ database features with YugabyteDB

New to distributed SQL or YugabyteDB? Read on.

What is Distributed SQL?

Distributed SQL databases are becoming popular with organizations interested in moving data infrastructure to the cloud or cloud native environments. This is often motivated by the desire to reduce TCO or move away from the horizontal scaling limitations of monolithic RDBMS like Oracle, PostgreSQL, MySQL, and SQL Server. The basic characteristics of Distributed SQL are:

  • They must have a SQL API for querying and modeling data, with support for traditional RDBMS features like foreign keys, partial indexes, stored procedures and triggers.
  • Smart distributed query execution so that query processing is pushed closer to the data as opposed to data being pushed over the network and thus slowing down query response times.
  • Should support automatic and transparent distributed data storage. This includes indexes which should be sharded across multiple nodes of the cluster so that no single node becomes a bottleneck. Data distribution ensures high performance and high availability.
  • Distributed SQL systems should also provide for strongly consistent replication and distributed ACID transactions.

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