| --- |
| name: Introduction |
| route: /docs/intro |
| --- |
| |
| ## What is Apache Superset? |
| |
| Apache Superset is a modern, enterprise-ready business intelligence web application. It |
| is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill |
| sets to explore and visualize their data, from simple pie charts to highly detailed deck.gl |
| geospatial charts. |
| |
| Here are a **few different ways you can get started with Superset**: |
| |
| - Download the [source from Apache Foundation's website](https://dist.apache.org/repos/dist/release/superset/1.0.0/) |
| - Download the latest Superset version from [Pypi here](https://pypi.org/project/apache-superset/) |
| - Setup Superset locally with one command |
| using [Docker Compose](installation/installing-superset-using-docker-compose) |
| - Download the [Docker image](https://hub.docker.com/r/apache/superset) from Dockerhub |
| - Install the latest version of Superset |
| [from Github](https://github.com/apache/superset/tree/latest) |
| |
| Superset provides: |
| |
| - An intuitive interface for visualizing datasets and crafting interactive dashboards |
| - A wide array of beautiful visualizations to showcase your data |
| - Code-free visualization builder to extract and present datasets |
| - A world-class SQL IDE for preparing data for visualization, including a rich metadata browser |
| - A lightweight semantic layer which empowers data analysts to quickly define custom dimensions and metrics |
| - Out-of-the-box support for most SQL-speaking databases |
| - Seamless, in-memory asynchronous caching and queries |
| - An extensible security model that allows configuration of very intricate rules on on who can access which product features and datasets. |
| - Integration with major authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, etc) |
| - The ability to add custom visualization plugins |
| - An API for programmatic customization |
| - A cloud-native architecture designed from the ground up for scale |
| |
| Superset is cloud-native and designed to be highly available. It was designed to scale out to large, |
| distributed environments and works very well inside containers. While you can easily test drive |
| Superset on a modest setup or simply on your laptop, there’s virtually no limit around scaling out |
| the platform. |
| |
| Superset is also cloud-native in the sense that it is flexible and lets you choose the: |
| |
| - web server (Gunicorn, Nginx, Apache), |
| - metadata database engine (MySQL, Postgres, MariaDB, etc), |
| - message queue (Redis, RabbitMQ, SQS, etc), |
| - results backend (S3, Redis, Memcached, etc), |
| - caching layer (Memcached, Redis, etc), |
| |
| Superset also works well with services like NewRelic, StatsD and DataDog, and has the ability to run |
| analytic workloads against most popular database technologies. |
| |
| Superset is currently run at scale at many companies. For example, Superset is run in Airbnb’s |
| production environment inside Kubernetes and serves 600+ daily active users viewing over 100K charts |
| a day. |
| |
| You can find a partial list of industries and companies embracing Superset |
| [on this page in GitHub](https://github.com/apache/superset/blob/master/RESOURCES/INTHEWILD.md). |