Citus Blog

Managing time series data at scale can be a challenge. PostgreSQL offers many powerful data processing features such as indexes, COPY and SQL—but the high data volumes and ever-growing nature of time series data can cause your database to slow down over time.

Fortunately, Postgres has a built-in solution to this problem: Partitioning tables by time range.

Partitioning with the Postgres declarative partitioning feature can help you speed up query and ingest times for your time series workloads. Range partitioning lets you create a table and break it up into smaller partitions, based on ranges (typically time ranges). Query performance improves since each query only has to deal with much smaller chunks. Though, you’ll still be limited by the memory, CPU, and storage resources of your Postgres server.

The good news is you can scale out your partitioned Postgres tables to handle enormous amounts of data by distributing the partitions across a cluster. How? By using the Citus extension to Postgres. In other words, with Citus you can create distributed time-partitioned tables. To save disk space on your nodes, you can also compress your partitions—without giving up indexes on them. Even better: the latest Citus 10.2 open-source release makes it a lot easier to manage your partitions in PostgreSQL.

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!

One of the big new things in Citus 10 is that you can now shard Postgres on a single Citus node. So in addition to using the Citus extension to Postgres to scale out Postgres across a distributed cluster, you can now also:

• Try out Citus on a single node with just a few simple commands
• Shard Postgres on a single Citus node to be “scale-out-ready”
• Simplify CI/CD pipelines by testing with single-node Citus

The Citus 10 release is chock full of new capabilities like columnar storage for Postgres, the open sourcing of the shard rebalancer, as well as the feature we are going to explore here: using Citus on a single node. No matter what type of application you run on top of Citus—multi-tenant SaaS apps, customer-facing analytics dashboards, time-series workloads, high-throughput transactional apps—there is something for everyone in Citus 10.

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.