Citus Use Cases

Multi-Tenant SaaS

SaaS apps grow fast, and need to scale while still providing a snappy user experience. Citus shards Postgres transparently at the data layer. And Citus makes it easy to add nodes & rebalance shards. So you can scale out as your app grows, without giving up Postgres.


Real-Time Analytics

Customer-facing dashboards need to provide sub-second responses to 1000s of concurrent users, while ingesting fresh data at the same time. Citus speeds up queries via parallelism, keeping more data in memory, higher I/O, & columnar compression.


Time Series

Time series workloads often need to grow beyond the resources of a single node. Capabilities such as the distributed query engine, columnar compression, parallel query, distributed DML… all combine to make Citus a good fit for time partitioned workloads.



Schema-based sharding allows distributing regular database schemas across many machines. This sharding methodology fits nicely with typical microservices architecture, where each microservice can have its own schema in a shared distributed database.


Why Use Citus To Scale Out Postgres? One Word: Performance.

Citus distributes and parallelizes Postgres workloads—and is often used as a system of record for SaaS apps and microservices, and as a system of engagement for analytics dashboards and time series data. Often, teams use the Citus database for mixed transactional & analytics workloads, to avoid managing multiple different databases. Others use Citus for high-throughput transactional apps. What Citus users have in common: performance really matters to them.

SaaS teams choose Citus to shard Postgres, to avoid the costs of sharding at the application layer. Developers building analytics dashboards tell us that distributed Postgres is a game changer, especially for time series data. Citus is a fit for many types of data-intensive apps, including geospatial analytics with PostGIS—plus video, web, and operational analytics dashboards. And the Citus columnar feature enables you to achieve compression ratios of 3x-10x or more.

How Citus Distributes Postgres

Watch Marco’s latest talk, inspired by SIGMOD

Video thumbnail: screen with Citus performance benchmarks

Learn how Citus works in this talk about Citus table types, the PostgreSQL extension APIs, the Citus query planner, and performance benchmarks comparing a multi-node Citus cluster to a single node.

These Segments Use Citus to Deliver Snappy Performance

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Rasty Turek pic

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

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