MetriQL
MetriQL
Headless metrics layer for consistent analytics
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Unify metric definitions across all data tools through a centralized platform that eliminates redundant redefinition for each analytics application. Integrate seamlessly with dbt projects automatically mapping resources as datasets and creating roll-up models, synchronize metrics reliably to business intelligence tools or access through REST APIs for embedded analytics, consume metrics in Python for data science workflows, leverage comprehensive documentation and tutorials for rapid implementation, and contribute to active development welcoming integrations, ideas, and community enhancements through GitHub collaboration.
Frequently Asked Questions
Is MetriQL free and open source?
Yes, MetriQL is open source. It is released under the Apache-2.0 license.
What can I use instead of Looker?
You can use MetriQL as a free, open-source alternative to Looker.
Can I self-host MetriQL?
Yes, MetriQL can be self-hosted on your own server or cloud infrastructure.
What is MetriQL written in?
It is built using Java, Kotlin, Jinja.
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