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What is Citus?

• Open-source PostgreSQL extension (not a fork)
• Scalable across multiple hosts through sharding and replication
• Distributed engine for query parallelization
• Highly available in the face of host failures

Citus horizontally scales PostgreSQL across commodity servers using sharding and replication. Its query engine parallelizes incoming SQL queries across these servers to enable real-time responses on large datasets.

Citus extends the underlying database rather than forking it, which gives developers and enterprises the power and familiarity of a traditional relational database. As an extension, Citus supports new PostgreSQL releases, allowing users to benefit from new features while maintaining compatibility with existing PostgreSQL tools. Note that Citus supports many (but not all) SQL commands; see the FAQ for more details.

Common Use-Cases:

• Powering real-time analytic dashboards
• Exploratory queries on events as they happen
• Large dataset archival and reporting
• Session analytics (funnels, segmentation, and cohorts)

To learn more, visit citusdata.com and join the mailing list to stay on top of the latest developments.

Quickstart

Local Citus Cluster

• Install docker-compose: Mac | Linux

• (Mac only) connect to Docker VM

  eval $(docker-machine env default)

• Pull and start the docker images

  wget https://raw.githubusercontent.com/citusdata/docker/master/docker-compose.yml
  docker-compose -p citus up -d

• Connect to the master database

  docker exec -it citus_master psql -U postgres -d postgres

• Follow the first tutorial instructions

• To shut the cluster down, run

  docker-compose -p citus down

Talk to Contributors and Learn More

Contributing

Citus is built on and of open source. We welcome your contributions, and have added a helpwanted label to issues which are accessible to new contributors. The CONTRIBUTING.md file explains how to get started developing the Citus extension itself and our code quality guidelines.

Who is Using Citus?

Citus is deployed in production by many customers, ranging from technology start-ups to large enterprises. Here are some examples:

• CloudFlare uses Citus to provide real-time analytics on 100 TBs of data from over 4 million customer websites. Case Study
• MixRank uses Citus to efficiently collect and analyze vast amounts of data to allow inside B2B sales teams to find new customers. Case Study
• Neustar builds and maintains scalable ad-tech infrastructure that counts billions of events per day using Citus and HyperLogLog.
• Agari uses Citus to secure more than 85 percent of U.S. consumer emails on two 6-8 TB clusters. Case Study
• Heap uses Citus to run dynamic funnel, segmentation, and cohort queries across billions of users and tens of billions of events. Watch Video

Copyright © 2012–2016 Citus Data, Inc.