24be6922fd
* [refactor] Remove dependency to personal fork of supercluster from mapbox visualizations - Update dependency to reference the vanilla supercluster - Clean up backend api call for mapbox vizzes to ensure a boolean is sent to indicate whether the viz includes custom metric for clustering - Refactor of mapbox and its cluster overlay components to use vanilla supercluster and its recommeded way for handling clustering based on custom aggregations. - Allow reclustering within the initial bounds on render in mapbox visualizations (stay true to old behaviors). - Remove the median aggregation from available cluster label aggregators as there is no memory efficient way to implement this and it is unknown how often this feature is used - Updating doc to mention the backward incompatible change re median * Perform the check for has_custom_metric through `not None` to produce a boolean and rename the field reflect it is a boolean. |
||
|---|---|---|
| contrib/docker | ||
| docs | ||
| install/helm/superset | ||
| scripts | ||
| superset | ||
| tests | ||
| .gitignore | ||
| .pylintrc | ||
| .travis.yml | ||
| CHANGELOG.md | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| ISSUE_TEMPLATE.md | ||
| LICENSE.txt | ||
| MANIFEST.in | ||
| README.md | ||
| UPDATING.md | ||
| alembic.ini | ||
| babel-node | ||
| gen_changelog.sh | ||
| pypi_push.sh | ||
| requirements-dev.txt | ||
| requirements.txt | ||
| setup.cfg | ||
| setup.py | ||
| tox.ini | ||
README.md
Superset
Apache Superset (incubating) is a modern, enterprise-ready business intelligence web application
[this project used to be named Caravel, and Panoramix in the past]
Screenshots & Gifs
View Dashboards
Slice & dice your data
Query and visualize your data with SQL Lab
Visualize geospatial data with deck.gl
Choose from a wide array of visualizations
Apache Superset
Apache Superset is a data exploration and visualization web application.
Superset provides:
- 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 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
Database Support
Superset speaks many SQL dialects through SQLAlchemy, a Python ORM that is compatible with most common databases.
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
- Clickhouse
- Apache Kylin
- 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 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 latency (real-time) data ingestion, flexible data exploration, and fast data aggregation. Existing Druid deployments have scaled to trillions of events and petabytes of data. Druid is best used to power analytic dashboards and applications.
Installation & Configuration
Resources
- Mailing list
- Gitter (live chat) Channel
- Docker image (community contributed)
- Slides from Strata (March 2016)
- Stackoverflow tag
- Join our Slack
- DEPRECATED Google Group
Contributing
Interested in contributing? Casual hacking? Check out 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!
- AiHello
- Airbnb
- Airboxlab
- Aktia Bank plc
- Amino
- Ascendica Development
- Astronomer
- Brilliant.org
- Capital Service S.A.
- Clark.de
- CnOvit
- Digit Game Studios
- Douban
- Endress+Hauser
- FBK - ICT center
- Faasos
- GfK Data Lab
- Konfío
- Lime
- Lyft
- Maieutical Labs
- [Myra Labs] (http://www.myralabs.com/)
- PeopleDoc
- Ona
- Pronto Tools
- Qunar
- ScopeAI
- Shopee
- Shopkick
- Tails.com
- THEICONIC
- Tobii
- Tooploox
- Udemy
- VIPKID
- Windsor.ai
- Yahoo!
- Zaihang
- Zalando