Distributed PostgreSQL as an extension
 
 
 
 
 
 
Go to file
Jelte Fennema 389086102a
Refactor 9 argument function to use a struct (#2952)
For another PR I needed to add another column which would require to add
another argument to an already 9 argument function signature. In this
case it would be a boolean flag and there were already two boolean flags
in there. In my experience it becomes really easy to mess up the order
of these flags at that point. Especially because the type system doesn't
distinguish between the 3 different booleans with completely different
meanings.

So I refactored these signatures to receive a struct containing most of
these arguments. Like that you don't mess up orderening, because the
meaning of the boolean is not order dependent but fieldname dependent.
It also makes it possible to set good shared defaults for this struct.
2019-09-13 15:49:53 +02:00
.circleci Introduce the adaptive executor (#2798) 2019-06-28 14:04:40 +02:00
.github Add DESCRIPTION to PR template 2018-12-12 05:35:12 +01:00
config Add citus_version(), analogous to PG's version() 2017-10-16 18:09:29 -06:00
src Refactor 9 argument function to use a struct (#2952) 2019-09-13 15:49:53 +02:00
.codecov.yml Remove obsolete lines 2017-09-25 11:18:25 -07:00
.editorconfig Better editorconfig 2019-09-12 16:40:25 +02:00
.gitattributes ruleutils_12.c 2019-08-22 18:56:05 +00:00
.gitignore Ignore compile_commands.json, fix typo 2019-06-26 10:32:01 +02:00
CHANGELOG.md Update Changelog for v8.3.2 2019-08-09 12:32:38 +03:00
CONTRIBUTING.md Update ubuntu dependencies in CONTRIBUTING (#2941) 2019-09-11 09:49:43 +02:00
LICENSE Add AGPL-3.0 in LICENSE file 2016-03-23 17:04:58 -06:00
Makefile Revert adb4669 2018-12-21 15:36:41 -07:00
Makefile.global.in Modernize coverage options 2019-02-26 22:20:31 -07:00
README.md updated Agari & MixRank user story links 2019-05-06 00:53:38 -07:00
aclocal.m4 Basic usage statistics collection. (#1656) 2017-10-11 09:55:15 -04:00
autogen.sh Changed product name to citus 2016-02-15 16:04:31 +02:00
configure pg12 revised layout of FunctionCallInfoData 2019-08-22 19:02:35 +00:00
configure.in pg12 revised layout of FunctionCallInfoData 2019-08-22 19:02:35 +00:00
github-banner.png Readme for 5.0 2016-03-18 13:32:13 -07:00
prep_buildtree Changed product name to citus 2016-02-15 16:04:31 +02:00

README.md

Citus Banner

Slack Status Latest Docs

What is Citus?

  • Open-source PostgreSQL extension (not a fork)
  • Built to scale out across multiple nodes
  • Distributed engine for query parallelization
  • Database designed to scale out multi-tenant applications, real-time analytics dashboards, and high-throughput transactional workloads

Citus is an open source extension to Postgres that distributes your data and your queries across multiple nodes. Because Citus is an extension to Postgres, and not a fork, Citus gives developers and enterprises a scale-out database while keeping the power and familiarity of a relational database. As an extension, Citus supports new PostgreSQL releases, and allows you to benefit from new features while maintaining compatibility with existing PostgreSQL tools.

Citus serves many use cases. Three common ones are:

  1. Multi-tenant & SaaS applications: Most B2B applications already have the notion of a tenant / customer / account built into their data model. Citus allows you to scale out your transactional relational database to 100K+ tenants with minimal changes to your application.

  2. Real-time analytics: Citus enables ingesting large volumes of data and running analytical queries on that data in human real-time. Example applications include analytic dashboards with sub-second response times and exploratory queries on unfolding events.

  3. High-throughput transactional workloads: By distributing your workload across a database cluster, Citus ensures low latency and high performance even with a large number of concurrent users and high volumes of transactions.

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

Getting started with Citus

The fastest way to get up and running is to deploy Citus in the cloud. You can also setup a local Citus database cluster with Docker.

Hyperscale (Citus) on Azure Database for PostgreSQL

Hyperscale (Citus) is a deployment option on Azure Database for PostgreSQL, a fully-managed database as a service. Hyperscale (Citus) employs the Citus open source extension so you can scale out across multiple nodes. To get started with Hyperscale (Citus), learn more on the Citus website or use the Hyperscale (Citus) Quickstart in the Azure docs.

Citus Cloud

Citus Cloud runs on top of AWS as a fully managed database as a service. You can provision a Citus Cloud account at https://console.citusdata.com and get started with just a few clicks.

Local Citus Cluster

If you're looking to get started locally, you can follow the following steps to get up and running.

  1. Install Docker Community Edition and Docker Compose
  • Mac:
    1. Download and install Docker.
    2. Start Docker by clicking on the applications icon.
  • Linux:
    curl -sSL https://get.docker.com/ | sh
    sudo usermod -aG docker $USER && exec sg docker newgrp `id -gn`
    sudo systemctl start docker
    
    sudo curl -sSL https://github.com/docker/compose/releases/download/1.11.2/docker-compose-`uname -s`-`uname -m` -o /usr/local/bin/docker-compose
    sudo chmod +x /usr/local/bin/docker-compose
    
    The above version of Docker Compose is sufficient for running Citus, or you can install the latest version.
  1. Pull and start the Docker images
curl -sSLO https://raw.githubusercontent.com/citusdata/docker/master/docker-compose.yml
docker-compose -p citus up -d
  1. Connect to the master database
docker exec -it citus_master psql -U postgres
  1. Follow the first tutorial instructions
  2. To shut the cluster down, run
docker-compose -p citus down

Talk to Contributors and Learn More

Documentation Try the Citus tutorial for a hands-on introduction or
the documentation for a more comprehensive reference.
Slack Chat with us in our community Slack channel.
Github Issues We track specific bug reports and feature requests on our project issues.
Twitter Follow @citusdata for general updates and PostgreSQL scaling tips.
Citus Blog Read our Citus Data Blog for posts on Postgres, Citus, and scaling your database.

Contributing

Citus is built on and of open source, and we welcome your contributions. 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:

  • Algolia uses Citus to provide real-time analytics for over 1B searches per day. For faster insights, they also use TopN and HLL extensions. User Story
  • Heap uses Citus to run dynamic funnel, segmentation, and cohort queries across billions of users and has more than 700B events in their Citus database cluster. Watch Video
  • Pex uses Citus to ingest 80B data points per day and analyze that data in real-time. They use a 20+ node cluster on Google Cloud. User Story
  • MixRank uses Citus to efficiently collect and analyze vast amounts of data to allow inside B2B sales teams to find new customers. User Story
  • Agari uses Citus to secure more than 85 percent of U.S. consumer emails on two 6-8 TB clusters. User Story
  • Copper (formerly ProsperWorks) powers a cloud CRM service with Citus. User Story

You can read more user stories about how they employ Citus to scale Postgres for both multi-tenant SaaS applications as well as real-time analytics dashboards here.


Copyright © 20122019 Citus Data, Inc.