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.
dbt State sits in PulseGate's Data integration & ETL category. 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 ships for the command line.
Behind dbt State is dbt Labs, and it 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. Among its 8 catalogued features are incremental builds, metadata checks, and compute cost reduction. dbt State is currently in beta.
Summary written by a language model from the project’s public pages.
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