Open-Source Databases · citusdata

citus

Citus is an open-source PostgreSQL extension that distributes data and queries across multiple nodes, enabling horizontal scaling for databases that outgrow a single server. It maintains PostgreSQL compatibility while adding sharding, columnar storage, and a distributed query engine.

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Source: GitHub — github.com/citusdata/citus

12.6k

GitHub stars

780

Forks

Primary language

AGPL-3.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	citusdata/citus
Owner	citusdata
Primary language	C
License	AGPL-3.0 — OSI-approved
Stars	12.6k
Forks	780
Open issues	1.1k
Latest release	v14.1.0 (2026-07-01)
Last updated	2026-07-08
Source	https://github.com/citusdata/citus

What citus is

Citus extends PostgreSQL with distributed table sharding, reference table replication, a distributed query router, columnar compression, and multi-node coordination. Written in C, it runs as a loadable extension and preserves PostgreSQL semantics for transactions, joins, and constraints across the cluster.

Quickstart

Get the citus source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/citusdata/citus.git2cd citus3# follow the project's README for install & configuration

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Best use cases

Multi-tenant SaaS applications

Scale customer data horizontally by sharding on tenant ID, isolating workloads and avoiding noisy neighbor problems while maintaining full SQL semantics.

Time-series and IoT data ingestion

Handle millions of events per second from devices by distributing writes across nodes and using columnar storage for efficient compressed analytics.

Real-time analytics at scale

Run complex aggregations, joins, and window functions in parallel across large datasets stored on a cluster, with query routing from any node.

Implementation considerations

Identify sharding key early: choice of distribution column is critical to avoid hotspots and cross-shard joins; schema refactoring post-deployment is expensive.
Network latency and bandwidth: inter-node communication overhead increases with cluster size and cross-shard query complexity; monitor and test with production-like data.
Backup and disaster recovery: multi-node clusters require distributed backup strategy; plan for coordinator and worker node failures.
Connection pooling: each worker node consumes connections; configure pooling to avoid connection saturation on large clusters.
Data rebalancing: moving shards across nodes during scaling requires careful planning to minimize downtime; test in staging first.

When to avoid it — and what to weigh

AGPL licensing constraints — If your deployment or product requires avoiding copyleft obligations, Citus's AGPL-3.0 license requires careful review; commercial licensing via Citus Data may be required for proprietary use.
Simple single-server workloads — Adding cluster complexity is unnecessary if your data fits on one PostgreSQL node with acceptable performance; evaluate scaling need before adoption.
Strict isolation or air-gapped requirements — Citus cluster setup and management require inter-node communication and coordination; highly restricted network environments may face operational friction.
Deeply nested or highly normalized schemas — Distributed joins across many tables or frequent cross-shard operations can add latency; star schemas and denormalization are better suited to Citus.

License & commercial use

Citus is licensed under AGPL-3.0 (GNU Affero General Public License v3.0), a copyleft license requiring source disclosure and license propagation for derivative works and network services.

Commercial use of Citus requires careful license analysis. AGPL-3.0 is a copyleft license; using Citus in a proprietary application or offering it as a service likely triggers disclosure obligations. Citus Data (the commercial entity behind the project) offers commercial licenses separate from the open-source version. Organizations must evaluate their deployment model—embedded use, managed service, or network-exposed—and obtain appropriate licensing or legal counsel. No assumption of commercial freedom should be made without explicit review.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Needs review
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

Standard PostgreSQL security applies (authentication, SSL, role-based access). Distributed query execution introduces data flow across network; node-to-node communication should be encrypted and restricted to private networks in production. No public security audit data provided. Cluster coordinator is a single point of control; compromise exposes all nodes. Regular patching for both PostgreSQL and Citus extension required. Organizations should review deployment architecture, network isolation, and backup/recovery procedures for data protection.

Alternatives to consider

Cockroach DB

Distributed SQL with ACID transactions and automatic sharding; proprietary licensing but no copyleft; more operational overhead for hybrid deployments.

Vitess (MySQL sharding middleware)

Open-source sharding proxy for MySQL; avoids tight schema coupling but requires explicit shard-aware queries and lacks Citus's integrated columnar storage.

Amazon Aurora (PostgreSQL compatible)

Managed PostgreSQL with read replicas and auto-scaling; simpler operations but limited horizontal write scaling; single-region latency constraints.

Software development agency

Build on citus with DEV.co software developers

Evaluate Citus for your distributed database needs. Test single-node deployment with Docker, review AGPL licensing requirements for your use case, and consult our team on cluster architecture and shard strategy.

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citus FAQ

Can I use Citus in a commercial product without releasing my code?

Not without additional licensing. AGPL-3.0 requires source disclosure for network services and derivative works. Contact Citus Data for commercial licensing options.

Do I need to rewrite my application to use Citus?

Not necessarily. Citus is a PostgreSQL extension, so existing SQL and most ORMs work. However, you should design sharding strategy upfront and use distribution UDFs (create_distributed_table) to enable scaling.

What happens if a worker node goes down?

Open-source Citus does not include automatic failover. Data on that node becomes unavailable; recovery requires manual intervention or external HA tooling (e.g., Patroni). Azure Cosmos DB for PostgreSQL provides automatic failover.

How do I handle uneven shard distribution?

Use the rebalance_table_shards() UDF to redistribute shards across worker nodes. This is an online operation but can impact performance; plan and test in staging.

Software development & web development with DEV.co

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