Citus Blog

Citus enables several different PostgreSQL use cases, but one of the most popular ones is to build scalable multi-tenant software as a service (SaaS) applications. The most common way to build a multi-tenant application on Citus is to distribute all your Postgres tables by a “tenant ID” column. That way rows are (hash-)distributed across nodes, while rows with the same tenant ID value are co-located on the same node for fast local joins, transactions, and foreign keys.

For those of you who build SaaS apps, one question many of you have is how active your tenants are. More specifically: What are your busiest tenants? How many queries is your application doing on behalf of your tenants, and how much CPU do those queries use?

The new 11.3 release to the open source Citus database extension gives you tenant monitoring—with instant visibility into your top tenants using the new citus_stat_tenants feature, which shows query counts and CPU usage over a configurable time period.

Citus is a distributed database that is built entirely as an open source PostgreSQL extension. In fact, you can install it in your PostgreSQL server without changing any PostgreSQL functionality. Citus simply gives PostgreSQL additional superpowers.

Being an extension also means we can keep adding new Postgres superpowers at a high pace. In the last release (11.0), we focused on giving you the ability to query from any node, opening up Citus for many new use cases, and we also made Citus fully open source. That means you can see everything we do on the Citus GitHub page (and star the repo if you’re a fan 😊). It also means that everyone can take advantage of shard rebalancing without write-downtime.

In the latest release (11.1), our Citus database team at Microsoft improved the application’s experience and avoided blocking writes during important operations like distributing tables and tenant isolation. These new capabilities built on the experience gained from developing the shard rebalancer, which uses logical replication to avoid blocking writes. In addition, we made the shard rebalancer faster and more user-friendly; also, we prepared for the upcoming PostgreSQL 15 release. This post gives you a quick tour of the major changes in Citus 11.1, including:

From the beginning of the COVID-19 pandemic, the United Kingdom (UK) government has made it a top priority to track key health metrics and to share those metrics with the public.

And the citizens of the UK were hungry for information, as they tried to make sense of what was happening. Maps, graphs, and tables became the lingua franca of the pandemic. As a result, the GOV.UK Coronavirus dashboard became one of the most visited public service websites in the United Kingdom.

The list of people who rely on the UK Coronavirus dashboard is quite long: government personnel, public health officials, healthcare employees, journalists, and the public all use the same service.

With the 10.1 release to the Citus extension to Postgres, you can now monitor the progress of an ongoing shard rebalance—plus you get performance optimizations, as well as some user experience improvements to the rebalancer, too.

Whether you use Citus open source to scale out Postgres, or you use Citus in the cloud, this post is your guide to what’s new with the shard rebalancer in Citus 10.1.

And if you’re wondering when you might need to use the shard rebalancer: the rebalancer is used when you add a new Postgres node to your existing Citus database cluster and you want to move some of the old data to this new node, to “balance” the cluster. There are also times you might want to balance shards across nodes in a Citus cluster in order to optimize performance. A common example of this is when you have a SaaS application and one of your customers/tenants has significant more activity than the rest.

Citus 10.1 is out! In this latest release to the Citus extension to Postgres, our team focused on improving your user experience. Some of the 10.1 fixes are operational improvements—such as with the shard rebalancer, or with citus_update_node. Some are performance improvements—such as for multi-row INSERTs or with citus_shards. And some are fixes you’ll appreciate if you use Citus with lots of Postgres partitions.

Given that the previous Citus 10 release included a bevy of new features—including things like columnar storage, Citus on a single node, open sourcing the shard rebalancer, new UDFs so you can alter distributed table properties, and the ability to combine Postgres and Citus tables via support for JOINs between local and distributed tables, and foreign keys between local and reference tables—well, we felt that Citus 10.1 needed to prioritize some of our backlog items, the kinds of things that can make your life easier.

This post is your guide to the what’s new in Citus 10.1. And if you want to catch up on all the new things in past releases to Citus, check out the release notes posts about Citus 10, Citus 9.5, Citus 9.4, Citus 9.3, and Citus 9.2.

If you have a large PostgreSQL database that runs on a single node, eventually the single node’s resources—such as memory, CPU, and disk—may deliver query responses that are too slow. That is when you may want to use the Citus extension to Postgres to distribute your tables across a cluster of Postgres nodes.

In your large database, Citus will shine for large tables, since the distributed Citus tables will benefit from the memory across all of the nodes in the cluster. But what if your Postgres database also contains some small tables which easily fit into a single node’s memory? You might be wondering: do you need to distribute these smaller tables, even though there wouldn’t be much performance gain from distributing them?

Fortunately, as of the Citus 10 release, you do not have to choose: you can distribute your large tables across a Citus cluster and continue using your smaller tables as local Postgres tables on the Citus coordinator.

One of the new features in Citus 10 that enables you to use a hybrid “local+distributed” Postgres database is that you can now JOIN local tables and distributed tables. (The other new Citus 10 feature has to do with foreign keys between local and reference tables.)

One of the main reasons people use Citus to transform Postgres into a distributed database is that with Citus, you can scale out horizontally while still enjoying PostgreSQL’s great RDBMS features. Whether you’re already a Postgres expert or are new to Postgres, you probably know one of the benefits of using a relational database is to have relations between your tables. And one of the ways you can relate your tables is of course to use foreign keys.

A foreign key ensures referential integrity, which can help you to avoid bugs in applications. For example, a foreign key can be used to ensure that a table of “orders” can only reference customer IDs that exist in the “customers” table.

If you have already heard about Citus 10, you know that Citus 10 gives you more support for hybrid data models, which means that you can easily combine regular Postgres tables with distributed Citus tables to get the best of the single node and distributed Postgres worlds.

This post will walk you through one of the new features in Citus 10: support for foreign keys between local Postgres tables and Citus reference tables.

Citus is an extension to Postgres that lets you distribute your application’s workload across multiple nodes. Whether you are using Citus open source or using Citus as part of a managed Postgres service in the cloud, one of the first things you do when you start using Citus is to distribute your tables. While distributing your Postgres tables you need to decide on some properties such as distribution column, shard count, colocation. And even before you decide on your distribution column (sometimes called a distribution key, or a sharding key), when you create a Postgres table, your table is created with an access method.

Previously you had to decide on these table properties up front, and then you went with your decision. Or if you really wanted to change your decision, you needed to start over. The good news is that in Citus 10, we introduced 2 new user-defined functions (UDFs) to make it easier for you to make changes to your distributed Postgres tables.

Last month we released Citus 10 and we’ve received an overwhelming amount of positive feedback on the new columnar compression and single node Citus features, as well as the news that we’ve open sourced the shard rebalancer.

The new and exciting Citus 10 features are bringing in lots of new users of Citus open source and the Citus database service on Azure. And many of you are asking:

One of the main reasons people use the Citus extension for Postgres is to distribute the data in Postgres tables across multiple nodes. Citus does this by splitting the original Postgres table into multiple smaller tables and putting these smaller tables on different nodes. The process of splitting bigger tables into smaller ones is called sharding—and these smaller Postgres tables are called “shards”. Citus then allows you to query the shards as if they were still a single Postgres table.

One of the big changes in Citus 10—in addition to adding columnar storage, and the new ability to shard Postgres on a single Citus node—is that we open sourced the shard rebalancer.

Yes, that’s right, we have open sourced the shard rebalancer! The Citus 10 shard rebalancer gives you an easy way to rebalance shards across your cluster and helps you avoid data hotspots over time. Let’s dig into the what and the how.