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Apache Superset

Apache Superset is a modern data exploration and visualization platform designed to be visual, intuitive, and interactive. It provides a rich set of data visualizations, a no-code chart builder, and a SQL editor with support for most SQL-speaking databases. Superset exposes a comprehensive REST API for programmatic access to dashboards, charts, datasets, databases, and user management. It is an Apache Software Foundation top-level project.

1 APIs 8 Features
AnalyticsBIDashboardData VisualizationSQLOpen Source

APIs

Apache Superset REST API

The Superset REST API v1 provides programmatic access to all Superset resources including dashboards (28 endpoints), charts (20 endpoints), datasets (19 endpoints), databases (3...

Features

No-Code Chart Builder

Drag-and-drop chart builder with 40+ visualization types requiring no coding.

SQL Lab

Browser-based SQL editor with query history, saved queries, and result export.

Dashboard Builder

Interactive dashboard composition with filters, tabs, and layout customization.

Semantic Layer

Centralized dataset definitions with virtual columns, metrics, and certification.

Row-Level Security

Fine-grained data access control with row-level security rules.

Embedded Dashboards

Embed Superset dashboards in external applications via iframe or SDK.

Alerts and Reports

Scheduled PDF/image reports and threshold-based alerts via email or Slack.

Database Connectivity

40+ database connectors via SQLAlchemy including BigQuery, Snowflake, and Redshift.

Use Cases

Business Intelligence Dashboards

Self-service BI dashboards for business users across operational and analytical data.

Data Exploration

Ad-hoc data exploration and visualization for data analysts.

Embedded Analytics

White-label analytics embedded in SaaS products and internal applications.

SQL-Based Reporting

Custom SQL-based reports and scheduled distribution.

Integrations

PostgreSQL

Native PostgreSQL support as both metadata database and data source.

Apache Druid

Druid connector for sub-second OLAP queries on time-series data.

BigQuery

Google BigQuery connector for cloud data warehouse analytics.

Snowflake

Snowflake connector for cloud analytics platform.

Apache Spark SQL

Spark SQL via Hive Thrift Server for distributed data analysis.

Slack

Slack integration for alerts and scheduled report delivery.

Apache Airflow

Airflow integration for orchestrating data pipeline and report schedules.

Resources

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GitHubRepository
GitHubRepository
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Documentation
Documentation
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Portal
Portal
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GettingStarted
GettingStarted
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ReleaseNotes
ReleaseNotes
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Support
Support
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TermsOfService
TermsOfService
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Python Package
SDK