PostgreSQL

YugabyteDB Engineering Update – April 13, 2020

YugabyteDB Engineering Update – April 13, 2020

We are excited to announce that YugabyteDB 2.1.3 is GA! You can read the official release notes here. This release shipped with over 60 new enhancements and fixes.

The Yugabyte team has been working from home in order to do our part with social distancing and to help with containment efforts. We have also transitioned to online meetings with our customers, partners, candidates, community, and fellow Yugabeings. We will continue with these and other measures until it’s determined to be safe otherwise.

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Scaling Relational Spring Microservices Without Load Balancers

Scaling Relational Spring Microservices Without Load Balancers

This article was originally posted on JAXenter.com.

Modern cloud native applications demand relational databases to be highly available while being able to scale to millions of requests (RPS) and thousands of transactions per second (TPS) on demand. This is becoming essential to meet the seamless experience demanded by business applications and their users. High availability and scalability in NoSQL databases like Apache Cassandra and MongoDB are well understood, but have been challenging problems to solve in relational databases.

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Scaling a Hasura GraphQL Backend with Distributed SQL

Scaling a Hasura GraphQL Backend with Distributed SQL

GraphQL is taking the modern development world by storm having been adopted by companies like Facebook, GitHub and Intuit because it solves many of the common problems developers encounter when working with REST APIs. For example, it solves issues like overfetching (getting more data than your response needs) and underfetching (having to make multiple fetches to get all the data you need), or when consolidating API responses on the client is necessary. When a developer follows the GraphQL spec,

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Distributed SQL Tips and Tricks – April 3, 2020

Distributed SQL Tips and Tricks – April 3, 2020

Welcome to this week’s tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation, and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub, or Stackoverflow. Ok, let’s dive right in:

How can I save the results of YSQL commands to a file?

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Automating YugabyteDB Deployments with Google Cloud Deployment Manager

Automating YugabyteDB Deployments with Google Cloud Deployment Manager

This is the second post in the Getting Started with YugabyteDB on Public Cloud series. In our first post, we covered Automating YugabyteDB Deployments with AWS CloudFormation templates. In this post we will show you how to achieve the same with Cloud Deployment Manager templates when using Google Cloud.

For redundancy across multiple fault domains inside a single region, Google Cloud uses the concept of zones,

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Basic CRUD Operations Using Hasura GraphQL with Distributed SQL on GKE

Basic CRUD Operations Using Hasura GraphQL with Distributed SQL on GKE

Editor’s note: This post was updated July 20, 2020 with new Helm and YugabyteDB versions

GraphQL is an MIT-licensed project originally developed at Facebook in 2012 and open-sourced a few years later. Two popular GraphQL projects, Hasura and Apollo, have reported download numbers of 29 and 33 million, respectively. Why? Think of GraphQL as a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API,

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An Introduction to Distributed SQL: Glossary of Terms

An Introduction to Distributed SQL: Glossary of Terms

In 2017 we introduced YugabyteDB, an open source, high performance, cloud native database for mission-critical applications. As a team, we have worked first hand on a number of databases such as Apache HBase, Apache Cassandra (from even before it was open sourced), Oracle, and RocksDB. We were the team that built and ran Facebook’s NoSQL platform that powered a number of user-facing, real-time applications. Over the years, we have had the opportunity and good fortune to become intimately familiar with what it takes to power mission-critical applications in a cloud-native architecture.

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Document Data Modeling in YugabyteDB with the JSON Data Types

Document Data Modeling in YugabyteDB with the JSON Data Types

YugabyteDB has two JSON data types, json and jsonb, to let you store documents in a column in a YSQL table and to do content-based queries with index support. YSQL is PostgreSQL compatible and it therefore supports every one of the rich set of about thirty five JSON-specific operators and functions that users of PostgreSQL’s JSON functionality might already know, and rely upon. These features let you handle semi-structured data,

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Getting Started with pgbench and Distributed SQL on GKE

Getting Started with pgbench and Distributed SQL on GKE

pgbench is a simple program for running benchmark tests on PostgreSQL. It runs the same sequence of SQL commands over and over, possibly in multiple concurrent database sessions, and then calculates the average transaction rate (transactions per second). By default, pgbench tests a scenario that is loosely based on TPC-B, involving five SELECT, UPDATE, and INSERT commands per transaction. However, it is easy to test other cases by writing your own transaction script files.

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YugabyteDB Engineering Update – March 17, 2020

YugabyteDB Engineering Update – March 17, 2020

We are excited to announce that YugabyteDB 2.1.2 is GA! You can read the official release notes here. This release shipped with over 30 new enhancements and fixes.

Before we dive in, we wanted to let you know that the Yugabyte team has been working from home in order to do our part with social distancing and to help with containment efforts. We have also transitioned to online meetings with our customers,

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