Ross ROSS = Recommend OSS · open-source software intelligence for agents

citusdata/citus

Distributed PostgreSQL as an extension observed · 2026-08-28

github.com/citusdata/citus · homepage · C · AGPL-3.0 (copyleft) observed · 2026-08-28

Health v2 · maintenance only

98/100

  • Activity 99
  • Release rhythm 96
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 17.5
  • age_days: 3866
  • days_rel: 27
  • days_push: 7
  • n_releases_24m: 13

Full methodology

Adoption not part of the score

12730 stars · 784 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Citus is an open-source PostgreSQL extension (written in C) that transforms Postgres into a distributed database by sharding tables across a cluster of nodes with a distributed query planner and executor. It supports row-based and schema-based sharding, reference tables, columnar storage, and querying from any node, all while remaining a Postgres extension rather than a fork.

Use cases

  • scale out a multi-tenant SaaS Postgres database by sharding on tenant_id
  • run sub-second analytical queries over billions of rows in real time
  • shard PostgreSQL horizontally without giving up SQL, joins, and transactions
  • use Postgres as a storage backend for microservices with distributed schemas
  • process large volumes of time series or IoT data for real-time analytics
  • add worker nodes and rebalance shards as data grows
  • compress and speed up scans with columnar storage on Postgres tables

When to choose

  • your multi-tenant SaaS app is hitting single-node Postgres limits on data size or concurrency
  • you need real-time analytics dashboards with sub-second responses over large datasets
  • you want horizontal scaling while keeping full SQL, ACID transactions, and the Postgres ecosystem
  • you want to stay in sync with new Postgres releases instead of running a fork
  • you need both transactional and analytical workloads on one database

When to avoid

  • your dataset fits comfortably on a single Postgres node with room to grow
  • you need a fully managed distributed database without operating your own cluster
  • your workload has no natural distribution key and doesn't fit schema-based sharding
  • you require a license more permissive than AGPL-3.0 for your product
  • you depend on Postgres features or extensions that Citus doesn't yet support on distributed tables

Facets

library · maturity active

database caching search-engine databases microservices big-data analytics backend cloud self-hosted postgresql-extension sharding distributed-sql multi-tenant columnar-storage horizontal-scaling real-time-analytics database-cluster linux macos docker

10 sources

Member repositories

RepositoryRoleHealth v2
citusdata/citusmain98

For agents

markdown · JSON · MCP: product_card(name="citusdata/citus")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem