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Metricflow Alternatives
Similar projects and alternatives to metricflow based on common topics and language
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dbt-core
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Apache Superset
Discontinued Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
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dictum
Describe business metrics with YAML, query and visualize in Jupyter with zero SQL
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dbt
Discontinued dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
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datafluent_pg
Build a better understanding of your data in PostgreSQL.
metricflow reviews and mentions
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Show HN: MetricFlow – open-source metric framework
Looks like it supports GraphQL APIs[1], and I guess downstream BI applications should be able to consume metric results from MetricFlow through GraphQL.
Three things:
First, MetricFlow does not currently support MySQL. We launched with support for BigQuery, Redshift, and Snowflake. I have opened an issue to add support for MySQL (and similar issues for other SQL engines are coming): https://github.com/transform-data/metricflow/issues/27
Second, what we call a data source is more similar to a table in a database, rather than the underlying database service itself. Metricflow itself is useful when you're using a single SQL engine - indeed, that's all we support today - but it is most useful when you're in a world where joins are a thing. That said, if you have one big data table you might still find it useful to have declarative metric definitions defined in Metricflow. Suppose, for example, you had a big NoSQL style table filled with JSON objects. You might define a few data sources that normalize those JSON objects into top level elements (identifiers, dimensions, aggregated measures) using the sql_query data source config attribute, and then that'd allow you to support structured queries on the data consumption end while pushing unstructured blobs from your application layer. This will be slow at query time, and only as reliable as the level of discipline exerted in your application development workflow, but it's possible.
Third, if we did support MySQL you'd basically connect to it via standard connection parameters - we have a config file where you can store the required information and then we'll manage the connections for you. However, I'm not familiar with uxwizz, and a quick perusal of their documentation did not turn up how one goes about connecting to the underlying DB. It's likely I just missed this, but at any rate I don't know how it is done. If they don't support standard MySQL client connections you'd need to write an adapter of some kind against whatever DB connection APIs they provide, in which case you'd likely need to roll a custom implementation of MetricFlow's SqlClient interface and initialize the MetricFlowEngine with that.
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A note from our sponsor - WorkOS
workos.com | 28 Mar 2024
Stats
dbt-labs/metricflow is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of metricflow is Python.