business intelligence / analytics dashboards
Metabase is an open-source business-intelligence platform that lets non-technical users explore SQL databases, build dashboards, write SQL, and embed analytics.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Python/BSD-2 self-hosted peer when you want SQL-first query-and-dashboard workflow without Metabase's Clojure/JVM footprint.
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
JVM/GPL-3 alternative when you need Tableau-style drag-and-drop visualization and can accept copyleft licensing.
🔥 人人可用的开源 BI 工具，数据可视化神器。An open-source BI tool alternative to Tableau.
Node/JS peer when dashboards must also pull from REST APIs and NoSQL, and be embedded in your own product.
Open-source reporting platform to build and share live dashboards from APIs, SQL and NoSQL databases, with powerful AI assistant, scheduling, and embeddable charts 📈📊
JVM/LGPL dashboard builder if your team is Java-centric and needs pure visualization over a question/card model.
DataGear数据可视化分析平台，自由制作任何您想要的数据看板
Apache-2.0 option for large-scale, embeddable analytics with a chart/dataset abstraction instead of Metabase's questions.
A modern, scalable analytics system
Python/AGPL choice when your data already lives in Frappe or ERPNext and you want native integration.
Open Source Business Intelligence Tool
Choose it when you need pixel-perfect paginated reports, multi-tenancy and row-level security out of the box.
Free, open source BI platform with AI conversational analytics (BYO-LLM), pixel-perfect paginated reports, interactive dashboards, SSO, embedding, multi-tenancy & row-level security. Every feature free in Community Edition. Self-hosted, Docker-ready
Java/Apache-2 self-service BI peer if you want a lighter stack than Metabase's Clojure runtime and comparable dashboards.
An easy to use, self-service open BI reporting and BI dashboard platform.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose it when BI should live in version-controlled markdown/SQL and deploy as a static site rather than a hosted query app.
Business intelligence as code: build fast, interactive data visualizations in SQL and markdown
Pick it when your warehouse is already dbt-modeled and metrics must be defined in code instead of a GUI model.
Agentic BI. Analytics at the speed of code ⚡️
Go/DuckDB single binary for fast local OLAP dashboards over files or warehouses instead of a server querying your DB live.
The fastest business intelligence tool for humans and agents.
Rust SQL-first BI for engineers who want transformations and charts committed in the repo, not a browser query builder.
Open-source BI for engineers
Headless semantic layer: use it behind your own frontend when you want governed metrics, not a finished BI UI.
📊 Cube Core is open-source semantic layer for AI, BI and embedded analytics
Pick it when dashboards are mostly metrics, logs and traces and you need alerting across observability datasources.
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Choose it if you want an LLM agent answering warehouse questions via CLI and chat instead of a clickable BI UI.
👾 nao is an open source analytics agent. (1) Create context with nao-core cli, (2) deploy nao chat interface for everyone
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Small Ruby drop-in for teams that only need SQL-driven dashboards and alerts, with none of Metabase's self-service query builder.
Business intelligence made simple
Notebook-plus-dashboard hybrid, but no push in over a year so it is only safe as an experiment.
Dashboards and notebooks in a single place. Create powerful and flexible dashboards using code, or build beautiful Notion-like notebooks and share them with your team.
These projects were analysed and named metabase among their alternatives. The relationship is not symmetric — how metabase rates them is a separate judgement, made when metabase is analysed in its own right.
calls metabase “Choose when non-technical users need point-and-click exploration and simpler setup than Superset.”
Apache Superset is a Data Visualization and Data Exploration Platform
calls metabase “Choose it for a GUI query builder and embedded analytics aimed at non-SQL users, rather than Redash's SQL-first editor.”
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
calls metabase “self-hosted GUI BI app aimed at nontechnical users; choose it for graphical ad-hoc analytics instead of a code project”
Business intelligence as code: build fast, interactive data visualizations in SQL and markdown