Apache Superset (incubating)¶
Apache Superset (incubating) is a modern, enterprise-ready business intelligence web application
Disclaimer: Apache Superset is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
Apache Superset, Superset, Apache, the Apache feather logo, and the Apache Superset project logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.
Apache Software Foundation Resources¶
A rich set of data visualizations
An easy-to-use interface for exploring and visualizing data
Create and share dashboards
Enterprise-ready authentication with integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuilder)
An extensible, high-granularity security/permission model allowing intricate rules on who can access individual features and the dataset
A simple semantic layer, allowing users to control how data sources are displayed in the UI by defining which fields should show up in which drop-down and which aggregation and function metrics are made available to the user
Integration with most SQL-speaking RDBMS through SQLAlchemy
Deep integration with Druid.io
The following RDBMS are currently suppored:
Other database engines with a proper DB-API driver and SQLAlchemy dialect should be supported as well.
- Installation & Configuration
- Getting Started
- Start with Docker
- OS dependencies
- Python virtualenv
- Python’s setup tools and pip
- Superset installation and initialization
- A proper WSGI HTTP Server
- Flask-AppBuilder Permissions
- Configuration behind a load balancer
- Database dependencies
- (AWS) Athena
- (Google) BigQuery
- Apache Drill
- Deeper SQLAlchemy integration
- Schemas (Postgres & Redshift)
- External Password store for SQLAlchemy connections
- SSL Access to databases
- DOMAIN SHARDING
- Celery Tasks
- Email Reports
- SQL Lab
- Celery Flower
- Building from source
- StatsD logging
- Install Superset with helm in Kubernetes
- Custom OAuth2 configuration
- Tutorial - Creating your first dashboard
- SQL Lab
- Visualizations Gallery
- Can I query/join multiple tables at one time?
- How BIG can my data source be?
- How do I create my own visualization?
- Can I upload and visualize csv data?
- Why are my queries timing out?
- Why is the map not visible in the mapbox visualization?
- How to add dynamic filters to a dashboard?
- How to limit the timed refresh on a dashboard?
- Why does ‘flask fab’ or superset freezed/hung/not responding when started (my home directory is NFS mounted)?
- What if the table schema changed?
- How do I go about developing a new visualization type?
- What database engine can I use as a backend for Superset?
- How can i configure OAuth authentication and authorization?
- How can I set a default filter on my dashboard?
- How do I get Superset to refresh the schema of my table?
- Is there a way to force the use specific colors?
- Does Superset work with [insert database engine here]?