Citus Blog

One of the top Citus features is the ability to run PostgreSQL at any scale, on a single node as well as a distributed database cluster.

As your application needs to scale, you can add more nodes to the Citus cluster, rebalance existing data to the new Postgres nodes, and seamlessly scale out. However, these operations require manual intervention: a) first you must create alerts on metrics, b) then, based on those alerts, you need to add more nodes, c) then you must kick off and monitor the shard rebalancer. Automating these steps will give you a complete auto scale experience—and make your life so much easier.

In this blog post, you will learn how to build a full-fledged auto scaling setup for the Citus database extension running as a managed service on Azure—called Azure Cosmos DB for PostgreSQL. You’ll also learn how you can easily add nodes to the Azure Cosmos DB for PostgreSQL cluster and use any metrics available to trigger actions in your cluster! Let’s dive into the following chapters:

If you’re building a software application that serves multiple tenants, you may have already encountered the challenges of managing and isolating tenant-specific data. That’s where the django-multitenant library comes in. This library, actively used since 2017 and now downloaded more than 10K times per month, offers a simple and flexible solution for building multi-tenant Django applications.

In this blog post, we’ll dive deeper into the concept of multi-tenancy and explore how Django-multitenant can help you build scalable, secure, and maintainable multi-tenant applications on top of PostgreSQL and the Citus database extension. We’ll also provide a practical example of how to use Django-multitenant in a real-world scenario. So, if you’re looking to simplify your multi-tenant development process, keep reading.

As you may have heard, we recently made PostgreSQL 15 generally available in Azure Cosmos DB for PostgreSQL within just 1 week of the PostgreSQL 15 release. The Postgres 15 version is available for you whether you need to create a new cluster in Azure Cosmos DB for PostgreSQL, or upgrade your existing cluster. (Note: you can do in-place major version upgrades in Azure Cosmos DB for PostgreSQL.) And the PostgreSQL 15 support is available in all Azure regions that support Azure Cosmos DB for PostgreSQL.

You may be surprised since it’s usually not the norm for a managed database service to start supporting the new major PostgreSQL version that early… This post will walk you through what’s going on behind the scenes that enables us to do such a feat. Some background before diving in:

Azure Cosmos DB for PostgreSQL is powered by native Postgres and Citus open source—and enables you to run PostgreSQL at any scale, from a single node to a large, distributed cluster. Customers can also scale out as much as they want depending on their needs with many additional features. The Hyperscale (Citus) managed service recently moved into Azure Cosmos DB family (more info on the launch of Azure Cosmos DB for PostgreSQL in this blog post) and with that introduced try Azure Cosmos DB for PostgreSQL for free where you can try out PostgreSQL 15 with Citus 11.1.

Big news from the Postgres and Citus team here at Microsoft! Just 1 week after PostgreSQL 15 was released, PostgreSQL 15 GA is generally available in the portal for the Azure Cosmos DB for PostgreSQL managed service—in all Azure regions. Whether you need to provision new clusters in Azure Cosmos DB for Postgres—or upgrade your existing database clusters—Postgres 15 is now a choice for you. Oh, and you can upgrade your existing cluster to Postgres 15 from any of the other supported major Postgres versions, using the in-place major version upgrade feature.

My main advice when running performance benchmarks for Postgres is: “Automate it!”

If you’re measuring database performance, you are likely going to have to run the same benchmark over and over again. Either because you want a slightly different configuration, or because you realized you used some wrong settings, or maybe some other reason. By automating the way you’re running performance benchmarks, you won’t be too annoyed when this happens, because re-running the benchmarks will cost very little effort (it will only cost some time).

However, building this automation for the database benchmarks can be very time-consuming, too. So, in this post I’ll share the tools I built to make it easy to run benchmarks against Postgres—specifically against the Citus extension to Postgres running in a managed database service on Azure called Hyperscale (Citus) in Azure Database for PostgreSQL.

Here’s your map for reading this post: each anchor link takes you to a different section. The first sections explore the different types of application workloads and their characteristics, plus the off-the-shelf benchmarks that are commonly used for each. After that you can dive into the “how to” aspects of using HammerDB with Citus and Postgres on Azure. And yes, you’ll see some sample benchmarking results, too.

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.

Today, we are excited to announce PostgreSQL 14’s General Availability (GA) on Azure’s Hyperscale (Citus) option. To our knowledge, this is the first time a major cloud provider has announced GA for a new Postgres major version on their platform one day after the official release.

Starting today, you can deploy Postgres 14 in many Hyperscale (Citus) regions. In upcoming months, we will roll out Postgres 14 across more Azure regions and also release it with our new Flexible Server option in Azure Database for PostgreSQL.

This announcement helps us bring the latest in Postgres to Azure customers as new features become available. Further, it shows our commitment to open source PostgreSQL and its ecosystem. We choose to extend Postgres and share our contributions, instead of creating and managing a proprietary fork on the cloud.

In this blog post, you’ll first get a glimpse into some of our favorite features in Postgres 14. These include connection scaling, faster VACUUM, and improvements to crash recovery times.

We’ll then describe the work involved in making Postgres extensions compatible with new major Postgres versions, including our distributed database Citus as well as other extensions such as HyperLogLog (HLL), pg_cron, and TopN. Finally, you’ll learn how packaging, testing, and deployments work on Hyperscale (Citus). This last part ties everything together and enables us to release new versions on Azure, with speed.

There is some good news for those of you wanting to shard your Postgres database in the cloud, so that as your data grows you have an easy way to scale out your Postgres database. I’m delighted to announce that Citus 10—the latest open source release of the Citus extension to Postgres—is now generally available in Hyperscale (Citus).

Hyperscale (Citus) is a built-in option in the Azure Database for PostgreSQL managed service, which has been around for a couple of years to help those of you who would rather focus on your application—and not on spending cycles managing your database.

It’s been an eventful time for Hyperscale (Citus) lately. If you’re interested in Postgres, distributed databases, and how to handle ever growing needs for your Postgres application or simply use Hyperscale (Citus), keep reading.

Citus is an open source extension to Postgres that enables horizontal scaling of your Postgres database. Citus distributes your Postgres tables, writes, and SQL queries across multiple nodes—parallelizing your workload and enabling you to use the memory, compute, and disk of a multi-node cluster. And Citus is available on Azure: Hyperscale (Citus) is a deployment option in Azure Database for PostgreSQL.

What’s really exciting to me is that we’ve made it easier and cheaper than ever to try and use Hyperscale (Citus). With Basic tier, you can now use Hyperscale (Citus) on a single node, parallelizing your operations and adopting a distributed database model from the very beginning. And you can now try Citus open source with a single docker run command—boom!

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.