The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

How YugabyteDB Scales to More than 1 Million Inserts Per Sec

There are a number of well-known experiments where eventually-consistent NoSQL databases were scaled out to perform millions of inserts and queries. Here, we do the same using YSQL, YugabyteDB’s PostgreSQL-compatible, strongly-consistent, distributed SQL API. We created a 100-node YugabyteDB cluster, ran single-row INSERT and SELECT workloads with high concurrency – each for an hour and measured the sustained performance (throughput and latency).

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Getting Started with PostgreSQL Triggers in a Distributed SQL Database

Triggers are a basic feature that all monolithic SQL systems like Oracle, SQL Server and PostgreSQL have supported for many years. They are very useful in a variety of scenarios ranging from simple audit logging, to advanced tasks like updating remote databases in a federated cluster. In this blog, we’ll look at examples of INSERT, UPDATE and INSTEAD OF triggers in Yugabyte DB.

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Announcing the Rook Operator for YugabyteDB

We are excited to congratulate the Rook community on the release on 1.1! We are also pleased to announce that the Rook operator for YugabyteDB is now available from and also on Github. This release extends the Rook storage operator as a custom resource, as well as provides an additional way to easily create, natively view and manage YugabyteDB within a Kubernetes cluster.

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Best Practices and Recommendations for Distributed SQL on Kubernetes

YugabyteDB and Kubernetes have very complementary design principles because they both rely on an extensible and flexible API layer, as well as a scale-out architecture for performance and availability. In this blog post we’ll look at best practices and recommendations when choosing Kubernetes as the cluster foundation for a distributed SQL system. This will begin with a review of relevant architectural decisions of the YugabyteDB.

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Getting Started with PGAdmin on a Distributed SQL Database

If you’re a database developer, you already understand the importance of a tool to manage your databases. Whether it is for creating schemas, ad-hoc querying, backups, or diving deeper to troubleshoot a database issue, a database tool can make your life much easier and increase your productivity. In a previous post we covered how to get started with DBeaver,

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PostgreSQL How To: Installing the Chinook Sample DB on a Distributed SQL Database

In this post we are going to walk you through how to download and install the PostgreSQL version of the Chinook sample DB on the YugaByte DB distributed SQL database with a replication factor of 3.

What’s YugaByte DB? It’s a high performance distributed SQL database for global, internet-scale apps. YugaByte DB is a PostgreSQL-compatible database.

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Getting Started with DBeaver on a Distributed SQL Database

Editor’s note: Updated July 7, 2020 with the new DBeaver wizard

If you’re a database developer, you know that you need different SQL statements for creating schemas, ad-hoc querying, initiating backups, or troubleshooting. For these scenarios, finding the right graphical tool can speed up these tasks and make you more productive. Over the years, the PostgreSQL community has developed several open source graphical tools for managing PostgreSQL databases,

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PostgreSQL How-to: SportsDB Running on a Distributed SQL Database

SportsDB is a sample dataset compiled from multiple sources, encompassing a variety of sports including football, baseball, ice hockey and more. It also cross-references many different types of content media. It is capable of supporting queries for the most intense of sports data applications, yet is simple enough for use by those with minimal database experience. The database itself is comprised of over 100 tables and just as many sequences,

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