Citus Blog

Development on Citus first started around a decade ago and once a year we release a major new Citus open source version. We wanted to make number 10 something special, but I could not have imagined how truly spectacular this release would become. Citus 10 extends Postgres (12 and 13) with many new superpowers:

• Columnar storage for Postgres: Compress your PostgreSQL and Citus tables to reduce storage cost and speed up your analytical queries.
• Sharding on a single Citus node: Make your single-node Postgres server ready to scale out by sharding tables locally using Citus.
• Shard rebalancer in Citus open source: We have open sourced the shard rebalancer so you can easily add Citus nodes and rebalance your cluster.
• Joins and foreign keys between local PostgreSQL tables and Citus tables: Mix and match PostgreSQL and Citus tables with foreign keys and joins.
• Functions to change the way your tables are distributed: Redistribute your tables in a single step using new alter table functions.
• Much more: Better naming, improved SQL & DDL support, simplified operations.

These new capabilities represent a fundamental shift in what Citus is and what Citus can do for you.

When I gave the kickoff talk in the Postgres devroom at FOSDEM this year, one of the Q&A questions was: “what’s happening with the Citus open source extension to Postgres?” The answer is, a lot. Since FOSDEM, Marco Slot and I have blogged about how Citus 9.2 speeds up large-scale htap workloads on Postgres, the Citus 9.3 release notes, and what’s new in Citus 9.4.

Now it’s time to walk through everything new in the Citus 9.5 open source release.

Our latest release to the Citus extension to Postgres is Citus 9.4. If you’re not yet familiar, Citus transforms Postgres into a distributed database, distributing your data and your SQL queries across multiple nodes. This post is basically the Citus 9.4 release notes.

If you’re ready to get started with Citus, it’s easy to download Citus open source packages for 9.4.

I always recommend people check out docs.citusdata.com to learn more. The Citus documentation has rigorous tutorials, details on every Citus feature, explanations of key concepts—things like choosing the distribution column—tutorials on how you can set up Citus locally on a single server, how to install Citus on multiple servers, how to build a real-time analytics dashboard, how to build a multi-tenant database, and more...

Our latest release to the Citus open source extension to Postgres is Citus 9.3.

If you’re a regular reader of the Citus Blog, you already know Citus transforms Postgres into a distributed database, distributing your data and SQL queries across multiple servers. This post—heavily inspired by the internal release notes that lead engineer Marco Slot circulated internally—is all about what’s new & notable in Citus 9.3.

Some of you have been asking, “what’s happening with the Citus open source extension to Postgres?” The short answer is: a lot. More and more users have adopted the Citus extension in order to scale out Postgres, to increase performance and enable growth. And you’re probably not surprised to learn that since Microsoft acquired Citus Data last year, our engineering team has grown quite a bit—and we’ve been continuing to evolve and innovate on the Citus open source extension.

Our newest release is Citus 9.2. We’ve updated the installation instructions on our Download page and in our Citus documentation, and now it’s time to take a walk through what’s new.

One of the primary challenges with scaling SaaS applications is the database. While you can easily scale your application by adding more servers, scaling your database is a way harder problem. This is particularly true if your application benefits from relational database features, such as transactions, table joins, and database constraints.

At Citus, we make scaling your database easy. Over the past year, we added support for distributed transactions, made Rails and Django integration seamless, and expanded on our SQL support. We also documented approaches to scaling your SaaS database to thousands of customers.

Today, we’re excited to announce the latest release of our distributed database—Citus 7.5. With this release, we’re adding key features that make scaling your SaaS / multi-tenant database easier. If you’re into bulleted lists, these features include the following.

Today, we’re excited to announce the latest release of our distributed database, Citus 7.4! Citus scales out PostgreSQL through sharding, replication, and query parallelization.

Ever since we open sourced Citus as a Postgres extension, we have been incorporating your feedback into our database. Over the past two years, our release cycles went down from six to four to two months. As a result, we have announced 10 new Citus releases, where each release came with notable new features.

Shorter release cycles and more features came at a cost however. In particular, we added new distributed planner and executor logic to support different use cases for multi-tenant applications and real-time analytics. However, we couldn’t find the time to refactor this new logic. We found ourselves accumulating technical debt. Further, our distributed SQL coverage expanded over the past two years. With each year, we ended spending more and more time on testing each new release.

In Citus 7.4, we focused on reducing technical debt related to these items. At Citus, we track our development velocity with each release. While we fix bugs in every release, we found that a full release focused on addressing technical debt would help to maintain our release velocity. Also, a cleaner codebase leads to a happier and more productive engineering team.

Today, we’re excited to announce Citus 7.3—the latest release of our distributed database that scales out Postgres. Citus 7.3 improves support for complex analytical queries, provides integration with Tableau and other BI tools, and integrates with the open source Postgres extension, TopN.

The features in this latest Citus database release are particularly important for real-time analytics workloads. In these workloads, users typically need to ingest data in real time and run analytical queries with sub-second response times. A good example is when you’re serving a dashboard to thousands of customers and your database needs to provide fast replies over billions of rows.

Here’s a quick overview of what’s new in Citus. For an overview of other recent Citus features, check out these blog entries about TopN for your Postgres database and Citus 7.2.

Today, we’re excited to announce our latest release of our distributed database—Citus 7.2. With this release, we’re making Citus more of a drop-in replacement for your single-node Postgres database, so you don’t need to adapt your SQL for a distributed system.

For multi-tenant applications where the single-tenant queries were scoped to a single machine, Citus already provided full SQL support. . The improvements in Citus 7.2 take our support for distributed SQL one big step further. With Citus database version 7.2, we now extend our distributed SQL support to queries that run on data spread across a cluster of machines. This becomes particularly important for real-time analytics workloads, where even the most complex SELECT queries need to be parallelized across machines.

If you’re into bulleted lists, here’s the quick overview of what’s new in Citus database version 7.2 for distributed queries that span across machines. For an overview of other recent Citus features check out these blogs about distributed transactions and Citus 7.1.

So about two weeks ago we had a stealth release of Citus 7.1. And while we have already blogged a bit about the recent (and exciting) update to our fully-managed database as a service–Citus Cloud—and about our newly-added support for distributed transactions, it’s time to share all the things about our latest Citus 7.1 release.

If you’re into bulleted lists, here’s the quick overview of what’s in Citus 7.1:

• Distributed transaction support
• Zero-downtime shard rebalancer
• Window function enhancements
• Distinct ON/count(distinct) enhancements
• Additional SQL enhancements
• Checking for new software updates