The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

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,

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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,

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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.

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Distributed SQL Tips and Tricks for PostgreSQL and Oracle DBAs – July 24, 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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GraphQL & Distributed SQL Tips and Tricks – July 10, 2020

Welcome to this week’s tips and tricks blog where we explore topics related to combining GraphQL and YugabyteDB to develop scalable APIs and services. We’ll also review upcoming events, new documentation, and blogs that have been published since the last tips and tricks post.

This next section is for those of you who might be new to either GraphQL or distributed SQL.

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INSERT INTO Yugabyte (We’re Hiring Developer Advocates)

It has been an exciting last few weeks here at Yugabyte! We closed our Series B funding round, Bill Cook (formerly of Pivotal and Greenplum) joined as our new CEO, we reaffirmed our commitment to open source, and achieved a bunch of cool community adoption milestones. We are hiring for several roles across engineering,

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Highly Available Prometheus Metrics for Distributed SQL with Thanos on GKE

In the last few years, Prometheus has gained huge popularity as a tool for monitoring distributed systems. It has a simple yet powerful data model and query language, however, it can often pose a bit of a challenge when it comes to high availability as well as for historical metric data storage. Adding more Prometheus replicas can be used to improve availability,

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Part 1: Deploying a Distributed SQL Backend for Apache Airflow on Google Cloud

Apache Airflow is a popular platform for programmatically authoring, scheduling, and monitoring workflows. Airflow has been deployed by companies like Adobe, Airbnb, Etsy, Instacart, and Square. The advantage of defining workflows as code is that they become more maintainable, versionable, testable, and collaborative. Airflow is used to author these workflows as directed acyclic graphs (DAGs) of tasks.

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