Lightdash
Open-source, dbt-native BI with metrics defined in code.
About
Lightdash is an open-source business intelligence platform that reads metric and dimension definitions directly from dbt projects instead of building a separate semantic layer. Definitions live in version-controlled dbt code while Lightdash provides the exploration interface, charts, dashboards, scheduled deliveries, and a SQL runner, connecting to Snowflake, BigQuery, Databricks, Postgres, Trino, ClickHouse, and more.
Its standout workflow is dbt Write-Back: metrics or models created in the Lightdash UI are automatically written back to the dbt project as pull requests, so changes still flow through code review and CI. An MCP server lets coding agents query the governed metric layer directly, which fits teams building analytics with AI assistance. It is MIT-licensed, with roughly 5,600 GitHub stars, and can be self-hosted for free or used via Lightdash Cloud.
What it can do
- Explore metrics and build dashboards from definitions synced with dbt
- Write-Back: UI-created metrics auto-generate GitHub/GitLab pull requests
- MCP server letting AI agents query the governed semantic layer
- Scheduled deliveries, metrics catalog, and multi-warehouse support
Setup
Self-host via Docker or sign up for Lightdash Cloud; connect your warehouse and point it at your dbt project.
Prerequisites
A dbt project (recommended for the full experience) and a supported data warehouse.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 97; Trending score 76/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.