Citus distributes your Postgres database across multiple nodes and parallelizes your queries and transactions. The combination of parallelism, keeping more data in memory, and higher I/O bandwidth often leads to dramatic speed ups. In this chart, we show a benchmark SQL query running ~40x faster with an 8-node Citus cluster vs. a single Postgres node.
By introducing new Postgres table types—distributed tables and reference tables—Citus makes it possible to distribute your data and queries across multiple nodes. In addition to the new table types, the Citus architecture includes a distributed Postgres query planner and an adaptive, distributed query executor. Distributed transactions are also supported. For many data-intensive use cases, scaling out Postgres with Citus can drive significant performance speed-ups.
Citus is an open source extension to Postgres (not a fork.) So when you use Citus, you’re still using Postgres under the covers, along with the Citus extension on top. To your application, running on a Citus distributed database is like running on top of a single Postgres node. And because Citus is an extension, it’s easy for us to keep Citus current with the latest Postgres releases—plus you get the performance benefits of horizontal scale, while still being able to leverage your familiar SQL toolset and your Postgres expertise.
One of the use cases that Citus is a good fit for is called “mixed transactional and analytical workloads.” Because Citus scales out Postgres horizontally—parallelizing your queries, allowing you to keep more data in memory, and giving you higher I/O bandwidth—Citus can meet the demanding performance requirements of these mixed workloads. So you can simplify your architecture by using a single database for your app’s transactional and analytical workloads, even for data-intensive applications. And you no longer have to accept a lag between when events occur and when your analytics dashboards can query the fresh data.
Find out more about the Citus concepts, architecture, cluster management, APIs, use cases, & performance tuning.
See how Citus scales out Postgres and parallelizes your workloads via these YouTube videos. Tip: turn on captions.
You can download and install Citus open source packages for Docker, Ubuntu, Debian, Fedora, CentOS, and Red Hat via these simple steps.
You can stand up a Citus cluster in minutes with the Hyperscale (Citus) option in the Azure Database for PostgreSQL managed service.
Using sharding and replication, the Citus open source extension to Postgres distributes your data and queries across multiple servers in a database cluster. Because Citus uses a coordinator as the single entry point for applications, your app can interact with the Citus cluster as if it were a single Postgres server.
Citus is available as an open source download and in the cloud as a managed service. The Hyperscale (Citus) option in Azure Database for PostgreSQL makes it easy to stand up a managed Citus cluster in minutes.
Citus 9.5 extension to Postgres
Citus 9.4 extension to Postgres
Citus 9.3, the extension that scales out Postgres horizontally
Citus 9.2 speeds up large scale HTAP workloads on Postgres
Using custom types with Citus & Postgres
How the Citus distributed query executor adapts to your Postgres workload
Making Postgres stored procedures 9X faster in Citus
Delivering 45x faster percentiles with Postgres, Citus, &
|Citus Version||Compatible with PostgreSQL|
|9.5||11, 12, 13|
Citus achieves order-of-magnitude faster execution compared to vanilla PostgreSQL through a combination of parallelism, keeping more data in memory, and higher I/O bandwidth.
Citus enables human real-time interaction with large datasets that span billions of records—and is a good fit for customer-facing workloads that often require low-latency response times. Performance increases as you add nodes to a Citus database cluster. Watch our 15-min performance demo from SIGMOD to see an example of how Citus speeds up Postgres.
The first step in migrating an application from Postgres to Citus is to choose your distribution column (sometimes called a distribution key, or a sharding key.) You’ll want to understand your workload in order to pinpoint a “good” distribution column, e.g., a column that enables you to get the maximum performance from Citus.
The second step is to prepare the Postgres tables and SQL queries for migration. The amount of effort involved depends (you’ve heard that before, right?) on whether your application is already centered around that distribution column in terms of queries and schema. If not, you may have to update some of your queries and/or add the distribution column to some of your tables.
If you are ready to delve deeper, the Migrating to Citus guide in the Citus documentation should be useful.
The Citus extension to Postgres is commonly used with customer-facing applications that are growing fast, have demanding performance requirements, are starting to experience slow queries, need to plan for future scale—or all of the above. Common use cases for Citus—both on-prem and in the cloud where Hyperscale (Citus) is an option in the Azure Database for PostgreSQL managed service—include:
As you’ll learn in the Citus concepts section of the documentation, Citus divides Postgres tables into multiple smaller tables, called shards. The shards are then spread across the nodes in the Citus database cluster when you configure Citus with the
create_distributed_table() function. When new data is ingested or when queries come in, the Citus coordinator routes them to the correct shards based on the value of the distribution column.
Another way of thinking about shards: Each shard contains a portion of the larger Postgres table that you have distributed. Imagine you previously had a 1 TB Postgres table. Now imagine you have distributed that 1 TB table across 100 shards in a Citus cluster. Each shard—which is just a smaller Postgres table—would be a 10 GB Postgres table.
Citus does more than simply shard and distribute your data, however. Citus also parallelizes your SQL queries across different nodes in the Citus cluster, giving you an order-of-magnitude increase in query response times for many use cases.