What is the standalone usecase for metricflow / Can metricflow be used without dbt cloud/semantic layer?

[janmechtel]

I'm trying to understand what the output of metricflow is.

On the hand I found many times that ones needs to have a dbt team/enterprise license and use dbt cloud to be able to query the metrics.

On the other hand Metricflow is described as a way to define metrics. How can one consume these metrics? For example is there a way to materialize certain metrics into a table?

This way having the definition of the metric in Metricflow/code would be much more readable and structured and would avoid to repeat the same definitions for different granularities/dimensions.

[AurelienLestienneNeoxia]

+1 would love clarification on the forecasted integration with dbt-core

[mirnawong1]

hey @janmechtel , that's a great question! I'll do my best to answer them cc @Jstein77

The dbt Semantic Layer is proprietary, however, some components of the dbt Semantic Layer are open source, like dbt-core and MetricFlow.

dbt Cloud Developer plans or dbt Core users can define metrics in their project, including a local dbt Core project, using the dbt Cloud IDE or the command line. You can do that in dbt Core and query your data warehouse locally using the MetricFlow commands (e..g mf) from your local dbt project.

However, to consume (or query metrics dynamically) metrics - you need the dbt Cloud API access and integration, which are available on a dbt Cloud Team or Enterprise plan.

We have an architecture page that provides a table description.

[janmechtel]

Thank you, I'm not sure how i missed those parts of the documentation. I searched quite thoroughly.

I'll look into whether we could use those metrics and maybe use dbt-metabase to sync them to metabase.