Distributed SQL

Run the REST Version of Spring PetClinic with Angular and Distributed SQL on GKE

Run the REST Version of Spring PetClinic with Angular and Distributed SQL on GKE

Java developers know that Spring Data makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. When YugabyteDB is combined with Spring, Java developers are able to leverage their familiarity with PostgreSQL while gaining the added benefits of distributed SQL. These “out-of-the-box” benefits include geo-data distribution, high performance, and horizontal scalability, which are impossible or difficult to achieve with monolithic SQL databases.

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My Time as a Yugabyte Software Engineering Intern

My Time as a Yugabyte Software Engineering Intern

February – A Unique Introduction

It was late February, and I had spent the past several weeks learning everything I could about the distributed database ecosystem. As an intern on the Investment Team at 8VC, I had gotten the chance to work on technical due diligence under Partner & CTO Bhaskar Ghosh, taking a multitude of pitches every week and constantly shifting contexts. One of those companies speaking with us was Yugabyte,

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Distributed SQL Tips and Tricks – Aug 17, 2020

Distributed SQL Tips and Tricks – Aug 17, 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 are secondary indexes stored internally in YugabyteDB?

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Staying Connected During COVID-19: Join Us at KubeCon + CloudNativeCon Europe 2020

Staying Connected During COVID-19: Join Us at KubeCon + CloudNativeCon Europe 2020

We are excited to sponsor KubeCon + CloudNativeCon Europe 2020 and participate alongside other open source and cloud native communities coming together to drive cloud native computing forward. Although many people across the world remain physically distanced (us included), we believe that coming together as a community and maintaining a sense of connection are still very essential and important. That’s why we are happy to take part in the virtual KubeCon + CloudNativeCon event taking place August 17-20,

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GraphQL & Distributed SQL Tips and Tricks – Aug 10, 2020

GraphQL & Distributed SQL Tips and Tricks – Aug 10, 2020

Welcome to this week’s tips and tricks blog where we explore both beginner and advanced topics on how to combine GraphQL and YugabyteDB to develop scalable APIs and services.

First things first, for those of you who might be new to either GraphQL or distributed SQL.

What’s GraphQL?

GraphQL is a query language for your API, and a server-side runtime for executing queries by using a type system you define for your data.

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Version Control for Distributed SQL Databases with Flyway

Version Control for Distributed SQL Databases with Flyway

Flyway is an open source database version control and migration tool that stresses simplicity and convention over configuration. Changes to the database can be written in SQL (and in some database-specific dialects like PL/SQL and T-SQL) or Java. You interact with Flyway using a command-line client, however there are a variety of plugins that can be leveraged, including Maven, Gradle, Spring Boot, and more.

Supported databases include Oracle, SQL Server, DB2,

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Distributed SQL Tips and Tricks – August 3, 2020

Distributed SQL Tips and Tricks – August 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:

Is there a way to get “updated_at”

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Distributed SQL Change Management with Liquibase and YugabyteDB on GKE

Distributed SQL Change Management with Liquibase and YugabyteDB on GKE

Liquibase is an open source and extensible change management project that supports a variety of databases including Snowflake, MySQL, and PostgreSQL via JDBC. Liquibase allows users to easily define changes in SQL, XML, JSON, and YAML. These changes are then managed in a version control system so the changes can be documented, ordered, and standardized. For more information on the features and benefits of Liquibase, check out their documentation site.

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Getting Started with SQLPad and Distributed SQL on Google Kubernetes Engine

Getting Started with SQLPad and Distributed SQL on Google Kubernetes Engine

SQLPad is an MIT licensed web app written in React and Node.js for writing and running SQL queries and visualizing the results. SQLPad supports PostgreSQL, MySQL, SQL Server, Crate, Vertica, Presto, SAP HANA, Cassandra, Snowflake, Google BigQuery, SQLite, and many more via ODBC. Because YugabyteDB is PostgreSQL compatible, most third-party tools and apps will work “out of the box.” SQLPad is no exception here.

In this blog post we’ll show you how to:

  • Install a 3 node YugabyteDB cluster on Google Kubernetes Engine
  • Build the sample Northwind database
  • Build and configure SQLPad
  • Start the required SQLPad processes
  • Launch the SQLPad UI and issue a test query to validate the deployment

New to distributed SQL or YugabyteDB?

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TPC-C Benchmark: 10,000 Warehouses on YugabyteDB

TPC-C Benchmark: 10,000 Warehouses on YugabyteDB

We are excited to announce that the TPC-C benchmark implementation for YugabyteDB is now open source and ready to use! While this implementation is not officially ratified by the TPC organization, it closely follows the TPC-C v5.11.0 specification.

For those new to TPC-C, the aim of the benchmark is to test how a database performs when handling transactions generated by a real-world OLTP application. This blog post shows the results of running the TPC-C benchmark in addition to outlining our experience of developing and running a TPC-C benchmark against YugabyteDB.

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