The Distributed SQL Blog

Thoughts on distributed databases, open source, and cloud native

Getting Started with IntelliJ IDEA and Distributed SQL

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.

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Use Retool to Quickly Build Distributed SQL and React Apps

Retool is a next generation WSIWYG SaaS-based tool that enables you to quickly build React applications for internal consumption from your existing data sources using a variety of pre-built “building blocks.” Developers can choose from over 58 drag and drop components and combine them with custom JavaScript to create applications that can be securely deployed on-premise or hosted environments like Heroku.

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What’s New and Improved in YugabyteDB Docs – September 2020

Welcome to this month’s edition of what’s new and improved in YugabyteDB Docs. We’re continually adding to and updating the documentation to give you the information you need to make the most out of YugabyteDB. This post covers recent content added, and changes made, to the YugabyteDB documentation since the last posting.

YSQL

What is YSQL?

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Distributed SQL Tips and Tricks for PostgreSQL and Oracle DBAs – Sep 9, 2020

Welcome to this week’s tips and tricks blog where we explore both beginner and advanced YugabyteDB topics for PostgreSQL and Oracle DBAs. First things first, for those of you who might be new to either distributed SQL or YugabyteDB.

What is Distributed SQL?

Distributed SQL databases are becoming popular with organizations interested in moving data infrastructure to the cloud or cloud native environments.

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Row Counts of Tables in a SQL Schema & Database – PostgreSQL and YugabyteDB

Getting total row counts of data in tables across various dimensions (per-table, per-schema, and in a given database) is a useful technique to have in one’s tool belt of SQL tricks. While there are a number of use cases for this, my scenario was to get the per-table row counts of all tables in PostgreSQL and YugabyteDB as a first sanity check after migrating an application with the pre-existing data from PostgreSQL to YugabyteDB.

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Using Envoy Proxy’s PostgreSQL & TCP Filters to Collect Yugabyte SQL Statistics

Layer 7 proxies like NGINX and HAProxy have been popular since the mid-2000s. The term “proxy” refers to their role as an intermediary for the traffic between an application client and an application server. The “layer 7” classification comes from the fact that these proxies take routing decisions based on URLs, IPs, TCP/UDP ports, cookies, or any information present in messages sent over a layer 7 (aka application layer) networking protocol like HTTP and gRPC.

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Webinar Recap: CRUD Operations with Hasura GraphQL and Distributed SQL

For those of you who missed last week’s YugabyteDB Community Q&A session, which covered GraphQL fundamentals, here’s the playback:

If you are interested in further exploring the possibilities of Hasura GraphQL and Distributed SQL, check out these resources.

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Getting Started with Hasura GraphQL Remote JOINs on Multi-Cloud Distributed SQL

Remote Joins in Hasura GraphQL extend the concept of joining data across tables, to being able to join data across tables and remote data sources. In this blog post we are going to demonstrate this capability by configuring the following set up.

  • A 3 node YugabyteDB cluster running on GKE with a Hasura GraphQL Engine attached
  • A 3 node YugabyteDB cluster running on AKS with a Hasura GraphQL Engine attached
  • A Remote Schema and Remote Relationship configured
  • The ability to issue GraphQL queries that join data from two different databases,

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