
Open-source metrics layer for your data warehouse
MetriQL is an open-source metrics store that lets you define your business metrics as code and share them consistently across all your BI and data tools. Built as an extension of dbt, it serves as a headless BI layer that centralizes metric definitions and syncs them to downstream tools via JDBC and REST APIs.
Define business metrics centrally in code using dbt-compatible YAML, ensuring a single source of truth across your organization
Works as a native extension of dbt, reading models directly from dbt's manifest.json artifact without requiring a separate transformation layer
Synchronize metric definitions to downstream BI tools including Tableau, Looker, Google Data Studio, and Google Sheets
Exposes a Trino/Presto-compatible JDBC driver so any BI tool that supports Trino can connect natively
Full REST API for building embedded analytics applications, custom dashboards, or integrating metrics into Python workflows
Automatically creates dbt roll-up models to pre-aggregate data, optimizing query performance and reducing warehouse costs
Reference measures and dimensions using MetriQL Query Language (MQL), which compiles to optimized SQL for your target data warehouse
Data teams define metrics once in code and share consistent definitions across Tableau, Looker, Google Sheets, and custom applications
Organizations building a modern data stack use MetriQL as the semantic layer between dbt transformations and multiple downstream BI consumers
Product teams leverage MetriQL's REST API to build embedded analytics dashboards within their SaaS applications without duplicating metric logic
Data engineers use automatic aggregation roll-ups to pre-compute common queries, reducing data warehouse compute costs and improving dashboard performance
Deploy on your own infrastructure with full control over data security, with no data ever leaving your data warehouse

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