提交 1ce3b81d 编写于 作者: M Maxime Beauchemin

Imporving the README

上级 89cd10b3
Please use [pull requests](https://github.com/airbnb/superset/pull/new/master)
to add your organization and/or project to this document!
Organizations
----------
- [Airbnb](https://github.com/airbnb)
- [GfK Data Lab](http://datalab.gfk.com)
- [Maieutical Labs](https://cloudschooling.it)
- [Shopkick](https://www.shopkick.com)
- [Amino](https://amino.com)
- [Faasos](http://faasos.com/)
- [Clark.de](http://clark.de/)
- [Yahoo!](www.yahoo.com)
- [Digit Game Studios](https://www.digitgaming.com/)
- [Brilliant.org](https://brilliant.org/)
- [Qunar](https://www.qunar.com/)
- [Udemy](https://www.udemy.com/)
- [Tooploox](https://www.tooploox.com/)
- [Tobii](http://www.tobii.com/)
- [Endress+Hauser](http://www.endress.com/)
- [Tails.com](https://tails.com)
- [FBK - ICT center](http://ict.fbk.eu)
Projects
----------
- None we know of yet
......@@ -19,8 +19,8 @@ Superset
width="500"
/>
**Superset** is a data exploration platform designed to be visual, intuitive
and interactive.
**Apache Superset** (incubating) is a modern, enterprise-ready
business intelligence web application
[this project used to be named **Caravel**, and **Panoramix** in the past]
......@@ -52,24 +52,26 @@ Screenshots & Gifs
![superset-query-search](https://cloud.githubusercontent.com/assets/130878/20234706/0f430a10-a835-11e6-8a0d-8b26cc2e6bbd.png)
Superset
---------
Superset's main goal is to make it easy to slice, dice and visualize data.
It empowers users to perform **analytics at the speed of thought**.
Apache Superset
---------------
Apache Superset is a data exploration and visualization web application.
Superset provides:
* A quick way to intuitively visualize datasets by allowing users to create
and share interactive dashboards
* A rich set of visualizations to analyze your data, as well as a flexible
way to extend the capabilities
* An intuitive interface to explore and visualize datasets, and
create interactive dashboards.
* A wide array of beautiful visualizations to showcase your data.
* Easy, code-free, user flows to drill down and slice and dice the data
underlying exposed dashboards. The dashboards and charts acts as a starting
point for deeper analysis.
* A state of the art SQL editor/IDE exposing a rich metadata browser, and
an easy workflow to create visualizations out of any result set.
* An extensible, high granularity security model allowing intricate rules
on who can access which features, and integration with major
authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER
through Flask AppBuilder)
* A simple semantic layer, allowing to control how data sources are
displayed in the UI, by defining which fields should show up in
which dropdown and which aggregation and function (metrics) are
made available to the user
on who can access which product features and datasets.
Integration with major
authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, ...)
* A lightweight semantic layer, allowing to control how data sources are
exposed to the user by defining dimensions and metrics
* Out of the box support for most SQL-speaking databases
* Deep integration with Druid allows for Superset to stay blazing fast while
slicing and dicing large, realtime datasets
* Fast loading dashboards with configurable caching
......@@ -78,15 +80,41 @@ Superset provides:
Database Support
----------------
Superset was originally designed on top of Druid.io, but quickly broadened
its scope to support other databases through the use of SQLAlchemy, a Python
Superset speaks many SQL dialects through SQLAlchemy, a Python
ORM that is compatible with
[most common databases](http://docs.sqlalchemy.org/en/rel_1_0/core/engines.html).
What is Druid?
-------------
From their website at http://druid.io
Superset can be used to visualize data out of most databases:
* MySQL
* Postgres
* Vertica
* Oracle
* Microsoft SQL Server
* SQLite
* Greenplum
* Firebird
* MariaDB
* Sybase
* IBM DB2
* Exasol
* MonetDB
* Snowflake
* Redshift
* **more!** look for the availability of a SQLAlchemy dialect for your database
to find out whether it will work with Superset
Druid!
------
On top of having the ability to query your relational databases,
Superset has ships with deep integration with Druid (a real time distributed
column-store). When querying Druid,
Superset can query humongous amounts of data on top of real time dataset.
Note that Superset does not require Druid in any way to function, it's simply
another database backend that it can query.
Here's a description of Druid from the http://druid.io website:
*Druid is an open-source analytics data store designed for
business intelligence (OLAP) queries on event data. Druid provides low
......@@ -130,19 +158,33 @@ Resources
* [Slides from Strata (March 2016)](https://drive.google.com/open?id=0B5PVE0gzO81oOVJkdF9aNkJMSmM)
Tip of the Hat
--------------
Superset would not be possible without these great frameworks / libs
* Flask App Builder - Allowing us to focus on building the app quickly while
getting the foundation for free
* The Flask ecosystem - Simply amazing. So much Plug, easy play.
* NVD3 - One of the best charting libraries out there
* Much more, check out the `install_requires` section in the [setup.py](https://github.com/airbnb/superset/blob/master/setup.py) file!
Contributing
------------
Interested in contributing? Casual hacking? Check out [Contributing.MD](https://github.com/airbnb/superset/blob/master/CONTRIBUTING.md)
Interested in contributing? Casual hacking? Check out
[Contributing.MD](https://github.com/airbnb/superset/blob/master/CONTRIBUTING.md)
Who uses Apache Superset (incubating)?
--------------------------------------
Here's a list of organizations who have taken the time to send a PR to let
the world know they are using Superset. Join our growing community!
- [Airbnb](https://github.com/airbnb)
- [Amino](https://amino.com)
- [Brilliant.org](https://brilliant.org/)
- [Clark.de](http://clark.de/)
- [Digit Game Studios](https://www.digitgaming.com/)
- [Endress+Hauser](http://www.endress.com/)
- [FBK - ICT center](http://ict.fbk.eu)
- [Faasos](http://faasos.com/)
- [GfK Data Lab](http://datalab.gfk.com)
- [Maieutical Labs](https://cloudschooling.it)
- [Qunar](https://www.qunar.com/)
- [Shopkick](https://www.shopkick.com)
- [Tails.com](https://tails.com)
- [Tobii](http://www.tobii.com/)
- [Tooploox](https://www.tooploox.com/)
- [Udemy](https://www.udemy.com/)
- [Yahoo!](www.yahoo.com)
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