The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

Why We Built YugabyteDB by Reusing the PostgreSQL Query Layer

Reusing PostgreSQL’s native query layer instead of writing a new PostgresQL-compatible query layer ground up has been one of the best design decisions we have made in YugabyteDB. As outlined in the challenges we faced building a distributed SQL database, we have battle scars to prove this insight – we started writing a PostgreSQL-compatible query layer from scratch before realizing that we simply cannot build the world’s best cloud native RDBMS in a timely manner if we persist down this path.

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Spanning the Globe without Google Spanner

Open Source Geo-Distributed Relational Database on Multi-Cluster Kubernetes

Google Spanner, conceived in 2007 for internal use in Google AdWords, has been rightly considered a marvel of modern software engineering. This is because it is the world’s first horizontally-scalable relational database that can be stretched not only across multiple nodes in a single data center but also across multiple geo-distributed data centers,

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Bringing Distributed SQL to VMware Tanzu

VMware Tanzu, the newest offering from VMware’s stable of proven enterprise products, brings together a portfolio of open source projects for modernizing applications and automating infrastructure management. VMware Tanzu provides a managed Kubernetes environment on VMware vSphere or any public cloud of choice that allows a consistent way to provision and deploy the code for application developers.

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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,

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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,

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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),

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INSERT INTO Yugabyte (We’re Hiring, April 2020)

Since our last hiring post, a lot has changed in the world around us (and even that is an understatement). The coronavirus is having a devastating effect on people and communities around the globe. Now more than a million people have gotten sick (or worse), many others are economically impacted, losing jobs, businesses are shutting down, and activities we perhaps once took for granted–everything from dining out,

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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,

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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.

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