Apache Superset

Superset uses 'DB engine specs' to manage how different databases interact with the platform. The level of support for a database is measured by a score and categorized by several key capabilities:

• SQL Basics: Fundamental SQL syntax support.
• Advanced SQL: Support for complex SQL features.
• Common Time Grains: Standard time granularity support (e.g., day, month).
• Extended Time Grains: Sub-hour or specific week variant time grains.
• Integrations: Integration with other platform components.
• Advanced Features: Support for specialized operational capabilities.

High-scoring databases like Presto, Trino, and Apache Hive typically offer broad support across most categories, while others may have partial support or lack specific advanced features.

The Superset Component Library is a collection of reusable, consistent, and accessible UI components used to build the Apache Superset user interface. It is organized into three primary categories:

• UI Components: Basic elements such as buttons, inputs, dropdowns, and other form elements.
• Chart Components: Visualization components used to render various types of charts and graphs.
• Layout Components: Structural elements used for page layout, including containers, grids, and navigation elements.

Note that the Component Library follows its own versioning scheme, which is independent of the main Apache Superset project versioning.

Apache Superset is a modern data exploration and visualization platform. Its core features include:

• No-code interface: For rapid chart building.
• SQL Editor: A web-based interface for advanced querying.
• Semantic Layer: A lightweight layer for defining custom dimensions and metrics.
• Database Support: Out-of-the-box support for nearly any SQL database or data engine.
• Visualizations: A wide array of visualizations, from simple bar charts to geospatial maps.
• Caching: A lightweight, configurable caching layer to reduce database load.
• Security: Extensible security roles and authentication options.
• API: A programmatic interface for customization.
• Architecture: A cloud-native architecture designed for scalability.

The Apache Superset MCP (Model Context Protocol) service provides a standardized way for AI assistants and automation tools to programmatically interact with Superset resources like dashboards, charts, datasets, and SQL Lab.

Key architectural characteristics:

• Separate Process: It runs as an independent process from the main Superset web server.
• Shared State: It uses its own Flask application instance and HTTP server but shares the same database and configuration as the main Superset application.
• Protocol: It uses the Model Context Protocol to expose Superset functionality as tools for AI agents.

Apache Superset provides several key resources for users to manage configuration, understand security, and track development:

• Feature Flags: Check the status of available Feature Flags to enable or disable specific functionalities.
• Standard Roles: Review how Role-Based Access Control (RBAC) permissions map to standard roles for security configuration.
• Superset SIPs: Track Superset Improvement Proposals (SIPs) to see the status of proposed features and implementations.
• Superset Wiki: Access community-driven best practices and additional information.
• Superset API: Refer to the REST API documentation for programmatic interaction with the platform.

When developing frontend components in Superset:

• Library Preference: Use Ant Design as the primary component library. Do not build a new component if Ant Design already provides one; instead, extend or customize it.
• Styling: Always use Emotion for styling and prefer using theme variables whenever applicable.
• Accessibility: Ensure all components are accessible by using official ARIA roles.

Superset extensions can extend the platform through several standardized contribution points:

• Custom UI Components: Adding new panels, views, and interactive elements to the interface.
• Commands and Menus: Implementing custom actions that appear in menus or are accessible via keyboard shortcuts.
• REST API Endpoints: Providing backend services that are hosted under the /extensions/ namespace.
• MCP Tools and Prompts: Integrating Model Context Protocol (MCP) capabilities to provide AI agent assistance.