Power of Postgres At Any Scale

All the Goodness of Postgres

With Citus you can use all your favorite Postgres features at scale, including data types, operators, functions, extensions, and indexes. Plus the reliability of Postgres and all the ongoing innovation in the Postgres community. Also, JSONB.

Postgres Tooling & Ecosystem

The Postgres ecosystem of tools, extensions, and libraries is vast. One of the reasons Citus is popular is because Citus is an extension to Postgres: therefore you get to leverage your Postgres expertise and use all of your familiar Postgres tools.

Relational Database Semantics

Citus offers relational database features like ACID transactions, joins, foreign key constraints, and SQL—to give you the flexibility of a relational database, at any scale.

Streaming Replication

The streaming replication feature in Postgres can be used to set up hot standby nodes with auto-failover for High Availability and read replicas for high-throughput read workloads.

Scale-Out Architecture

Packaged as a Postgres Extension

Because Citus is an extension to Postgres and not a fork, Citus can easily stay current with the latest releases of Postgres, allowing you to benefit from all of the latest innovations in Postgres.

Database Sharding

Citus transparently shards your Postgres tables across multiple nodes to give your application more memory, compute, and disk storage. Which gives you parallelism, high performance, and a way to keep scaling as your application grows.

Single-node Citus

Be “scale-out-ready” by sharding your data on a single Citus node, using a distributed data model from the start—so you can easily add nodes later. Or use single-node Citus as a handy way to try out Citus.

Easy to add nodes

It’s simple to add nodes to Citus, whether starting with Citus on a single node, or using Citus on a distributed cluster.

Shard Rebalancer

When adding nodes to a Citus cluster, the zero-downtime shard rebalancer enables you to redistribute shards across old and new worker nodes to better balance the data distribution and the performance of your Citus database.

Fast relational operations

Using advanced data placement and replication features, Citus gives you the fastest possible experience for relational database features like joins, foreign keys, subqueries, and stored procedures.

Rails & Django integration

Like Postgres, Citus is compatible with all the popular programming languages. And for Rails and Django we’ve created gems and libraries to make it easy for your application to adapt to a sharded, distributed Postgres database.

Tenant Isolation

Multi-tenant SaaS applications sometimes need to isolate the shards for a large customer to ensure that the large customer gets the resources they need and doesn’t negatively impact performance for everyone else. Hence: tenant isolation.

Distributed SQL Engine

Distributed Query Engine

Citus takes an incoming SQL query, plans the query for parallel execution, and pushes down the parallel computations to the nodes in the database cluster. As you add nodes, Citus automatically distributes queries to leverage all the memory and cpu cores available.

Adaptive Query Executor

The Citus distributed query executor dynamically adapts to the type of distributed SQL query, and uses a dynamic pool of connections to each worker node to execute Postgres queries on the shards.

Distributed Transactions

Citus provides atomic transactions across shards and nodes with advanced techniques like 2PC recovery and distributed deadlock detection to give you a seamless database experience.

Parallel Query

Parallelize analytical queries across the Citus distributed database cluster for maximum performance, giving your application the memory, compute, and higher IO bandwidth of multiple nodes.

Columnar Storage

With the new Citus 10 columnar feature, you can compress regular Postgres tables and/or distributed tables to reduce disk footprint, reduce I/O bandwidth needs, and speed up analytics queries.

Multiple Table Types

With Citus you can use a mix of distributed tables (with co-location), reference tables, and local Postgres tables—so you can optimize performance by sharding large tables; placing often-referenced tables on all the Citus nodes; and keeping the smaller tables local to the coordinator.

Monitoring & Management

Monitoring Metrics

Citus utilities can be used to query Citus table and relation sizes. The popular pg_stat_statements gives visibility into statistics about queries that are running on the database. And many customers integrate their favorite monitoring tools with Postgres and Citus.

Distributed Explain

The Postgres EXPLAIN feature creates a query plan for each query it receives and is invaluable in optimizing performance. In Citus, we’ve created a distributed EXPLAIN feature that performs the same function in the context of a distributed database.

Per-Tenant Landlord Monitoring

The citus_stat_statements feature in Citus gives insights into query activity and per-tenant use of database resources, allowing you to determine cost per tenant, identify load hotspots, & optimize/tune performance as needed.

Fine-Grained Access Controls

Granular access controls in Citus enable you to limit capabilities to certain types of users to control user access and reduce risk.

Enterprise SLA & 24x7 Support

For those who’ve already purchased Citus Enterprise, on-call support is included 24x7, as well as professional services to get you up and running. Citus Enterprise also includes an SLA to ensure you have the support you need.

Data Types & Extensions


PostgreSQL and Citus support 40+ data types, including semi-structured data types and JSONB. Many developers cite the JSONB support in Postgres as a super effective way to store unstructured data and documents in the database.

Custom Types

Custom types—also called user-defined types—are a super useful Postgres feature. In a Citus distributed cluster, custom types (as well as Postgres extensions) are automatically propagated to new and existing worker nodes, without any special steps on your part.


PostGIS is an extension to Postgres that adds support for geographical objects to Postgres, allowing location queries to be run in SQL. Open source, freely available, and works with Citus.

HyperLogLog (HLL)

HLL is an algorithm for the count-distinct problem and can approximate the number of distinct elements in a set. With sketch algorithms for probabilistic distincts such as HLL, you can provide deeper analytics in real-time across petabytes of data.


t-digest is a sketch algorithm for accurately estimating quantiles and percentiles. Originally created by Ted Dunning back in 2013, there is now a popular Postgres extension for t-digest too.


TopN is an open source PostgreSQL extension for calculating the most frequently occurring values in a column, and is part of the class of probabilistic distinct algorithms called sketch algorithms.

Full Text Search

Full text search in Postgres enables you to search documents, parts of documents, and semi-structured data using regular expressions and text search from within your Citus database.

Run Citus Anywhere

Open Source

We’re on a mission to make it so you no longer have to worry about scaling your database. With Citus open source, you extend your Postgres database with superpowers like distributed tables, a distributed SQL query engine, columnar storage, and the ability to use Citus on a single node.

In the Cloud

Convenience trumps all, and many Citus users tell us they would rather focus on their application and not on managing their database. So Citus is available in the cloud as a managed service with Azure Cosmos DB for PostgreSQL.

Customers ask how many weeks they have to wait for results, but with Citus it takes us roughly three minutes. The difference is so striking compared to our competitors, customers usually struggle to understand how we can do it.

Rasty Turek, Founder and CEO, Pex

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