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.
Apache Superset publishes 1 API on the APIs.io network: REST API. Tagged areas include Analytics, BI, Dashboard, Data Visualization, and SQL.
Apache Superset’s developer surface includes documentation, developer portal, getting-started guide, release notes, support, and 6 more developer resources.
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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...
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FinOps
Apache Superset Finops
FINOPSFeatures
Drag-and-drop chart builder with 40+ visualization types requiring no coding.
Browser-based SQL editor with query history, saved queries, and result export.
Interactive dashboard composition with filters, tabs, and layout customization.
Centralized dataset definitions with virtual columns, metrics, and certification.
Fine-grained data access control with row-level security rules.
Embed Superset dashboards in external applications via iframe or SDK.
Scheduled PDF/image reports and threshold-based alerts via email or Slack.
40+ database connectors via SQLAlchemy including BigQuery, Snowflake, and Redshift.
Use Cases
Self-service BI dashboards for business users across operational and analytical data.
Ad-hoc data exploration and visualization for data analysts.
White-label analytics embedded in SaaS products and internal applications.
Custom SQL-based reports and scheduled distribution.
Integrations
Native PostgreSQL support as both metadata database and data source.
Druid connector for sub-second OLAP queries on time-series data.
Google BigQuery connector for cloud data warehouse analytics.
Snowflake connector for cloud analytics platform.
Spark SQL via Hive Thrift Server for distributed data analysis.
Slack integration for alerts and scheduled report delivery.
Airflow integration for orchestrating data pipeline and report schedules.
Resources
Get Started 2
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use