dbt State is a tool for dbt that checks metadata and model SQL on every run, building only models that have changed. This reduces warehouse compute costs, speeds up data workflows, and ensures fresher analytics data. It is designed for data engineers using dbt Core or dbt Cloud to optimize their data pipelines.
In the Other infrastructure space, dbt State takes a focused approach. It eliminates unnecessary data model rebuilds, reducing compute costs and improving data freshness for analytics workflows. dbt State is a B2B product aimed at data engineers. It runs on the command line.
Behind dbt State is dbt Labs, and the product first shipped in 2016. The project is developed in the open on GitHub with 13k stars and 2.9k commits in the last 90 days. Across PulseGate's embedding index, dbt State has few near neighbours, marking it as relatively distinct. Among its 8 catalogued features are incremental builds, metadata checks, and compute cost reduction. dbt State is currently in beta.
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