Topics / #bi

Bi projects on GitHub

Business intelligence platforms for dashboards, analytics, and data exploration.

As of , the most-starred Bi projects on GitHub are superset (75.2K stars), metabase (49.7K stars) and redash (28.8K stars). GitHub.Locker tracks 6 Bi repositories with 186.3K stars combined. The fastest-growing on October 16 was superset, with +16 stars in a day.

6Projects
186.3KStars in total
+37Stars in a day

Hot right now

Most stars gained in a day · Oct 16

The all-time top

6 projects · by stars

  1. #1 · apache/superset

    superset

    Apache Superset is a modern, enterprise-ready business intelligence web application for data exploration and visualization: build dashboards, charts, and query data with a built-in SQL editor.

    75.2K
  2. #2 · metabase/metabase

    metabase

    Metabase is an open-source business intelligence tool that lets anyone on a team ask questions about data and build dashboards without knowing SQL.

    49.7K
  3. #3 · getredash/redash

    redash

    Redash is an open-source business intelligence platform: you connect data sources, explore and query them, visualize the results and share dashboards with your team. Thousands of organizations use it for data-driven decisions.

    28.8K
  1. 4

    cube

    21Kcube-js/cube · Rust

    An open-source semantic layer: define metrics, dimensions, joins and access rules once in code, and it serves them through SQL, REST and GraphQL APIs to BI tools, custom apps and AI agents.

  2. 5

    perspective

    11.3Kperspective-dev/perspective · Rust

    Perspective is an interactive data visualization and analytics component built for large, real-time and streaming datasets. It ships as a Custom Element UI (grid, charts, pivots) backed by a streaming query engine that runs in-browser via WebAssembly or server-side in Python, Node.js and Rust.

  3. 6

    graphene

    215graphene-data/graphene · TypeScript

    Graphene is an everything-as-code analytics framework built specifically for coding agents: it adds a SQL semantic layer and a dashboard file format so an agent can answer data questions and build polished visualizations instead of a human clicking around a BI tool.

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