Apache Superset is a Data Visualization and Data Exploration Platform
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feat(datasource): Checkbox for always filtering main dttm in datasource (#25204)
Co-authored-by: Elizabeth Thompson <eschutho@gmail.com>
2023-09-14 15:57:08 -07:00
.github docs: update security policy and add CVE info (#24769) 2023-07-26 14:21:26 +01:00
RELEASING chore: deprecate FLASK_ENV and improve conf.ENVIRONMENT_TAG_CONFIG (#24404) 2023-06-29 12:04:32 -07:00
RESOURCES docs: Add wattbewerb to users list (#24962) 2023-08-11 14:27:58 -03:00
docker fix: Bumps Flask Caching to fix RCE vulnerability (#25090) 2023-08-31 08:44:48 -03:00
docs docs: rewrite superset docker localhost prose (#25296) 2023-09-14 09:31:56 -03:00
helm/superset fix: Bumps Flask Caching to fix RCE vulnerability (#25090) 2023-08-31 08:44:48 -03:00
requirements fix: Bumps Flask Caching to fix RCE vulnerability (#25090) 2023-08-31 08:44:48 -03:00
scripts chore(pre-commit): Add pyupgrade and pycln hooks (#24197) 2023-06-01 12:01:10 -07:00
superset feat(datasource): Checkbox for always filtering main dttm in datasource (#25204) 2023-09-14 15:57:08 -07:00
superset-embedded-sdk fix(embedded sdk): Remove trailing slash from passed superset domain if there is one (#25020) 2023-08-25 09:24:58 -07:00
superset-frontend feat(datasource): Checkbox for always filtering main dttm in datasource (#25204) 2023-09-14 15:57:08 -07:00
superset-websocket build(deps): bump ws from 8.13.0 to 8.14.1 in /superset-websocket (#25293) 2023-09-14 09:49:54 -07:00
tests feat(datasource): Checkbox for always filtering main dttm in datasource (#25204) 2023-09-14 15:57:08 -07:00
.asf.yaml feat: bump to Python3.9 (#23890) 2023-05-10 20:21:56 +03:00
.codecov.yml refactor(monorepo): change coverage of core to 100% (#17698) 2021-12-14 16:19:55 +08:00
.dockerignore feat: Containerize WebSocket server (#14514) 2021-05-10 09:28:50 -07:00
.editorconfig Adding editorconfig setting for IDE hints (#10855) 2020-09-14 08:19:23 -07:00
.flaskenv chore: deprecate FLASK_ENV and improve conf.ENVIRONMENT_TAG_CONFIG (#24404) 2023-06-29 12:04:32 -07:00
.fossa.yml Update FOSSA configuration for new requirements layout (#10848) 2020-09-16 13:28:04 -07:00
.gitattributes fix: Normalise `*.sh` File Endings (#16608) 2021-09-13 16:25:15 -07:00
.gitignore feat: improve color consistency (save all labels) (#19038) 2022-03-21 15:20:04 +08:00
.gitmodules ci: set remote URL to https and bump sha (#14350) 2021-04-26 17:43:32 +01:00
.markdownlint.json feat(helm): Support for flower and websocket containers (#21806) 2022-10-27 13:03:21 -07:00
.pre-commit-config.yaml fix: Error when using the legacy dataset editor (#25057) 2023-08-23 09:10:17 -03:00
.pylintrc fix: Python3.11 (str, Enum) issue (#24803) 2023-07-31 09:04:09 -07:00
.rat-excludes feat: Upgrade documentation V2 (#17411) 2022-01-27 14:54:53 -08:00
CHANGELOG.md chore: back port 2.1.1 doc changes (#25165) 2023-09-06 09:14:32 -07:00
CODE_OF_CONDUCT.md chore: using bitly to manage expiring Slack invitation links (#22631) 2023-01-12 14:31:19 -07:00
CONTRIBUTING.md fix: Bumps Flask Caching to fix RCE vulnerability (#25090) 2023-08-31 08:44:48 -03:00
Dockerfile build(docker): bump geckodriver and firefox to latest (#25287) 2023-09-14 14:23:48 -07:00
INSTALL.md Fix wrong filename mentioned in INSTALL.md (#14630) 2021-06-29 11:40:26 +03:00
LICENSE.txt chore: pre-commit run --all-files (#10500) 2020-08-02 14:32:17 -07:00
MANIFEST.in Update MANIFEST.in (#9261) 2020-03-25 22:00:41 -07:00
Makefile feat: bump to Python3.9 (#23890) 2023-05-10 20:21:56 +03:00
NOTICE docs: remove (some) references to incubating/incubation (#12284) 2021-01-06 13:40:40 -08:00
README.md feat: adding Scarf pixels to gather telemetry on readme and website (#25065) 2023-08-24 08:44:05 -06:00
UPDATING.md chore: back port 2.1.1 doc changes (#25165) 2023-09-06 09:14:32 -07:00
docker-compose-non-dev.yml fix: docker-compose non-dev (#25055) 2023-08-22 11:35:10 -03:00
docker-compose.yml chore: isolate examples database by default (#25003) 2023-08-17 11:50:24 +01:00
dockerize.Dockerfile build(docker): add dockerize image (#24534) 2023-06-29 12:03:59 -07:00
lintconf.yaml feat(helm): Support for flower and websocket containers (#21806) 2022-10-27 13:03:21 -07:00
pytest.ini feat: support nulls in the csv uploads (#10208) 2020-07-06 13:26:43 -07:00
setup.cfg fix: Bumps Flask Caching to fix RCE vulnerability (#25090) 2023-08-31 08:44:48 -03:00
setup.py fix: Bumps Flask Caching to fix RCE vulnerability (#25090) 2023-08-31 08:44:48 -03:00
superset_text.yml chore(build): creating default superset_text.yaml placeholder file (#24250) 2023-06-04 22:37:33 -06:00
tox.ini fix: Revert tox basepython (#24124) 2023-05-19 06:40:38 -07:00

README.md

Superset

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Superset

A modern, enterprise-ready business intelligence web application.

Why Superset? | Supported Databases | Installation and Configuration | Release Notes | Get Involved | Contributor Guide | Resources | Organizations Using Superset

Why Superset?

Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

Superset provides:

  • A no-code interface for building charts quickly
  • A powerful, web-based SQL Editor for advanced querying
  • A lightweight semantic layer for quickly defining custom dimensions and metrics
  • Out of the box support for nearly any SQL database or data engine
  • A wide array of beautiful visualizations to showcase your data, ranging from simple bar charts to geospatial visualizations
  • Lightweight, configurable caching layer to help ease database load
  • Highly extensible security roles and authentication options
  • An API for programmatic customization
  • A cloud-native architecture designed from the ground up for scale

Screenshots & Gifs

Video Overview

https://user-images.githubusercontent.com/64562059/234390129-321d4f35-cb4b-45e8-89d9-20ae292f34fc.mp4


Large Gallery of Visualizations


Craft Beautiful, Dynamic Dashboards


No-Code Chart Builder


Powerful SQL Editor


Supported Databases

Superset can query data from any SQL-speaking datastore or data engine (Presto, Trino, Athena, and more) that has a Python DB-API driver and a SQLAlchemy dialect.

Here are some of the major database solutions that are supported:

redshift google-biquery snowflake trino presto databricks druid firebolt timescale rockset postgresql mysql mssql-server db2 sqlite sybase mariadb vertica oracle firebird greenplum clickhouse exasol monet-db apache-kylin hologres netezza pinot teradata yugabyte starrocks

A more comprehensive list of supported databases along with the configuration instructions can be found here.

Want to add support for your datastore or data engine? Read more here about the technical requirements.

Installation and Configuration

Extended documentation for Superset

Get Involved

Contributor Guide

Interested in contributing? Check out our CONTRIBUTING.md to find resources around contributing along with a detailed guide on how to set up a development environment.

Resources

Superset 2.0!

Understanding the Superset Points of View