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apache/superset

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73,451 stars·17,689 forks·TypeScript·Apache-2.0·44 viewssuperset.apache.org↗

Superset

Superset is a web-based business intelligence platform designed for data exploration, visualization, and interactive dashboarding. It functions as a query-driven analytics engine that connects to various SQL databases, allowing users to perform ad-hoc analysis, define virtual metrics, and build complex data visualizations through a centralized interface.

The platform distinguishes itself through a robust semantic layer that transforms raw database schemas into calculated columns and virtual metrics, enabling consistent business logic across an organization. It features a plugin-based visualization architecture that supports modular chart components and custom geospatial maps, alongside granular role-based access control that enforces data security through row-level filters applied directly to generated SQL queries.

Beyond its core analytics capabilities, the system provides comprehensive tools for enterprise data governance, including automated reporting, scheduled data snapshots, and secure content embedding. It supports high-performance operations through distributed caching, asynchronous query execution, and a standardized API for programmatic resource management.

The project is designed for production-grade deployment, offering extensive configuration for containerized environments, metadata management, and secure network communication. It provides detailed documentation for installation, environment migration, and system hardening to ensure scalability and data integrity across distributed instances.

Features

  • Business Intelligence Platforms - Delivers a web-based analytics environment for connecting to databases to explore, visualize, and share data through interactive reports.
  • Interactive Dashboards - Displays data from connected databases through real-time, interactive web-based dashboards.
  • SQL-Based Analytics Engines - Translates user-defined metrics and filters into database-specific SQL queries for real-time data retrieval and analysis.
  • Data Exploration - Enables ad-hoc SQL querying and advanced data transformations to inspect and analyze large datasets within a web interface.
  • Enterprise Data Portals - Acts as a centralized hub for managing organizational data assets, enforcing security policies, and distributing automated reports.
  • Database Connection Managers - Handles database connection credentials and drivers to link external SQL data sources to a centralized management platform.
  • SQL Query Execution - Executes database queries, manages session history, formats SQL code, and exports results while tracking performance metrics.
  • Role-Based Access Control - Enforces data security by mapping user identities to granular permissions and row-level filters applied to database queries.
  • Semantic Metrics - Defines virtual metrics and aggregations that apply business logic directly to raw data sources.
  • SQL-Based Semantic Layer - Maps raw database schemas to virtual metrics and calculated columns using dynamic SQL templating to enforce business logic.
  • Dashboard Resource Management - Maintains dashboard metadata, chart definitions, and configuration settings through standard create, read, update, and delete operations.
  • Dynamic Query Contexts - Injects user-specific attributes and security roles into queries to enforce row-level data access policies.
  • Dashboard Access Controls - Controls dashboard visibility by assigning specific access roles to users for associated charts and datasets.
  • Data Visualization - Renders complex datasets into interactive graphical representations including charts, maps, and tabular views.
  • Automated Reporting - Schedules recurring data snapshots and alerts for automated delivery to stakeholders via email or messaging platforms.
  • Query Result Caching - Caches frequent query results in memory to minimize latency and accelerate dashboard rendering.
  • Enterprise - Centralizes governance by applying security policies and metadata management across large-scale organizational data.
  • SQL Templating Engines - Embeds dynamic user context and filter parameters directly into SQL queries prior to execution.
  • Database Configurations - Configures production-grade database connections and backend parameters to store application metadata securely.
  • Database Schema Migrations - Automates the application of versioned updates to database schemas to maintain compatibility after software upgrades.
  • Asynchronous Query Execution - Offloads long-running database queries to background workers to prevent web request timeouts.
  • API Request Authentication - Validates API requests using JSON web tokens and manages session tokens to ensure secure communication between clients and the backend.
  • OAuth Providers - Connects external identity providers to internal roles for streamlined authentication and user access management.
  • Background Task Schedulers - Triggers recurring background operations like report generation and data synchronization at defined intervals.
  • Plugin-Based Visualization Architecture - Supports a registry system for loading custom visualization components and geospatial charts into the interface.
  • Table Visualizations - Organizes data into structured tabular views by grouping information and defining custom metrics.
  • Visualization and Analysis - Enterprise-ready business intelligence and data exploration platform.
  • Analytics - Modern platform for data exploration and interactive visualization.
  • Analytics Tools - Listed in the “Analytics Tools” section of the Awesome Selfhosted awesome list.
  • Business Intelligence - Enterprise-ready platform for business intelligence and data visualization.
  • Business Intelligence and Analytics - Modern data exploration and visualization platform.
  • Databases and Storage - Data exploration and visualization platform.
  • Dashboards - Enterprise-ready data exploration and visualization platform.
  • Interactive Data Grids - Facilitates tabular data exploration with server-side filtering and comparative time-shift analysis capabilities.
  • Metadata Storage Management - Persists chart definitions, user profiles, and activity logs within a relational database for configuration consistency.
  • Database Administration Interfaces - Provides integrated interfaces for browsing database schemas and managing complex data queries.
  • Secrets Management - Protects session data and sensitive metadata through robust cryptographic secret key management.
  • Root Initialization Utilities - Initializes the application environment through automated database migrations, administrative account setup, and server startup routines.
  • Asynchronous Task Queueing - Delegates resource-intensive processing to background workers to ensure web interface responsiveness.
  • Alert and Report Configuration - Distributes automated data alerts and visual reports by bridging notification channels with headless browser snapshots.
  • Advanced Analytics Functions - Calculates complex metrics like rolling averages and time-series comparisons directly within charts to provide deeper analytical insights.
  • Cache Timeout Management - Balances data freshness and performance by allowing granular control over cache expiration policies.
  • Metadata-Driven Configurations - Synchronizes application state and security policies across distributed instances by storing them in a central database.
  • Migration Guidance - Guides users through configuration updates and schema changes required when upgrading between major versions.
  • Row Level Security - Filters data visibility by applying role-based SQL constraints to ensure users access only permitted rows.
  • Secure Network Communication - Guarantees secure network communication by mandating encrypted protocols for all data transit.
  • SQL Query Schedulers - Manages periodic query execution by defining metadata schemas that dictate report timing and delivery destinations.
  • WSGI Servers - Deploys production-ready server environments with asynchronous workers to manage concurrent user requests.
  • Content Sharing and Embedding - Produces permanent links for dashboard states and filter configurations to simplify the sharing of interactive visual content.
  • Distributed Caches - Stores frequently accessed query results in shared memory layers to accelerate retrieval and improve horizontal scalability.
  • Query Parameter Filters - Parses input parameters into SQL-compatible clauses to ensure dynamic and secure database querying.
  • Container Orchestration - Standardizes multi-service environments by deploying consistent, containerized images across diverse infrastructure targets.
  • Custom Container Images - Packages specialized container images pre-configured with essential database drivers and dependencies for production deployment.
  • Multi-Architecture Images - Supports diverse deployment environments by providing container images compatible with multiple hardware architectures.
  • Automated Notifications - Dispatches automated alerts and reports through background workers configured for email or messaging delivery.
  • Webhook Notification Delivery - Pushes structured alert payloads to external HTTP endpoints to facilitate seamless integration with automated notification workflows.
  • Distributed Coordination Services - Leverages distributed key-value stores to manage locking mechanisms and real-time event notifications across multiple nodes.
  • API Key Authentication - Issues long-lived authentication tokens to grant programmatic access to service accounts while respecting user-defined permission levels.
  • Production Security Hardening - Hardens production environments by enforcing credential rotation and secure management of sensitive configuration keys.
  • CORS Policy Configurations - Permits controlled interaction with the application interface by specifying allowed origins for cross-domain requests.
  • Content Security - Restricts browser-side resource loading to specific trusted domains to prevent unauthorized script execution and data injection.
  • Embedded Data Visualizations - Embeds custom data dashboards into external web portals through secure, configurable integration interfaces.
  • Dashboard Embedding - Integrates interactive data visualizations into third-party portals using secure embedding configurations and dedicated software development kits.

Star history

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Frequently asked questions

What does apache/superset do?

Superset is a web-based business intelligence platform designed for data exploration, visualization, and interactive dashboarding. It functions as a query-driven analytics engine that connects to various SQL databases, allowing users to perform ad-hoc analysis, define virtual metrics, and build complex data visualizations through a centralized interface.

What are the main features of apache/superset?

The main features of apache/superset are: Business Intelligence Platforms, Interactive Dashboards, SQL-Based Analytics Engines, Data Exploration, Enterprise Data Portals, Database Connection Managers, SQL Query Execution, Role-Based Access Control.

What are some open-source alternatives to apache/superset?

Open-source alternatives to apache/superset include: cube-js/cube — Cube is a semantic data layer that provides a unified framework for defining business metrics, dimensions, and… dbt-labs/dbt-core — dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control.… plausible/analytics — This project is an open-source, privacy-focused web analytics platform designed for high-throughput data ingestion and… apache/incubator-superset — This project is a business intelligence suite and SQL data visualization platform used for data analysis, reporting,… getredash/redash — Redash is a self-hosted analytics platform and SQL data visualization tool. It provides a web-based SQL query editor… lightdash/lightdash — Lightdash is an open-source business intelligence platform that treats analytics logic as code. It centralizes metric…