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Burak Yucesoy 3cf1ef06c0 Use custom compiled PostgreSQL on push builds 
Previously we compiled PostgreSQL for PR and we used already compiled
PostgreSQL packages for push builds. Compiling PostgreSQL allows us to
run isolation/vanilla tests. Thus we only ran those tests for PR builds.
We did not used compiled PostgreSQL for both builds because;
- We wanted to run our tests against packages
- Compiling takes too much time.

However, there are some benefits in using custom compiled PostgreSQL
in push builds instead of PR builds such as;
- At the moment, we do not run isolation/vanilla tests until we open a
PR, which does not make any sense.
- After merging a PR (i.e. after push to the master) push builds run
and we do not run isolation tests.
- While merging community to enterprise, we have to open a temporary
PR to make travis run isolation/vanilla tests.
- With this change master branch will have its own cache that means
every branch originated from master branch can re-use master branch's
cache. (Currently we cannot use cache for the first PR build)

With this PR we switch from using custom compiled for PR builds to push
builds.
 		2017-11-01 06:29:59 -07:00
config Add citus_version(), analogous to PG's version() 2017-10-16 18:09:29 -06:00
src Use list_length() != 1 in SingleReplicatedTable(). 2017-10-31 21:51:43 -04:00
.codecov.yml Remove obsolete lines 2017-09-25 11:18:25 -07:00
.editorconfig Set tab size for GitHub display 2017-03-22 13:03:39 -06:00
.gitattributes Add ruleutils file for PostgreSQL 11 2017-09-25 17:20:24 -07:00
.gitignore Add vim swap files to .gitignore 2017-07-12 14:16:23 +02:00
.travis.yml Use custom compiled PostgreSQL on push builds 2017-11-01 06:29:59 -07:00
CHANGELOG.md Add CHANGELOG entry for 7.0.3 2017-10-16 11:40:51 +03:00
CONTRIBUTING.md Two more libs I needed to build citus 2017-08-24 13:04:35 -06:00
LICENSE Add AGPL-3.0 in LICENSE file 2016-03-23 17:04:58 -06:00
Makefile Fix VPATH builds broken in 087d8427e3. 2017-04-25 16:04:42 -07:00
Makefile.global.in Basic usage statistics collection. (#1656) 2017-10-11 09:55:15 -04:00
README.md Update README.md 2017-03-23 11:00:32 -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 Make reports hostname configurable and enable stats collection in tests. 2017-10-31 21:51:43 -04:00
configure.in Make reports hostname configurable and enable stats collection in tests. 2017-10-31 21:51:43 -04:00
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

Build Status Slack Status Latest Docs

What is Citus?

  • Open-source PostgreSQL extension (not a fork)
  • Scalable across multiple machines through sharding and replication
  • Distributed engine for query parallelization
  • Database designed to scale multi-tenant applications

Citus is a distributed database that scales across commodity servers using transparent sharding and replication. Citus extends the underlying database rather than forking it, giving developers and enterprises 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. Two common ones are:

  1. Multi-tenant database: 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 subsecond response times and exploratory queries on unfolding events.

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

Getting started with Citus

The fastest way to get up and running is to create a Citus Cloud account. You can also setup a local Citus cluster with Docker.

Citus Cloud

Citus Cloud runs on top of AWS as a fully managed database as a service and has development plans available for getting started. 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 application’s 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.
Google Groups The Citus Google Group is our place for detailed questions and discussions.
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.

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:

  • 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 © 2012–2017 Citus Data, Inc.