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dbt-polars

A dbt adapter that runs models locally using Polars. Instead of connecting to a database, dbt-polars reads and writes files — on your local filesystem, Azure Blob Storage, AWS S3, or an Iceberg catalog.

Installation

pip install dbt-polars

Extra dependencies are required for cloud and Iceberg backends:

pip install 'dbt-polars[azure]'    # Azure Blob Storage
pip install 'dbt-polars[s3]'       # AWS S3
pip install 'dbt-polars[iceberg]'  # Apache Iceberg (SQLite, REST, Databricks, …)

Catalogs

dbt-polars uses catalogs to define where data is stored. Each catalog maps to a storage backend. You can configure multiple catalogs in a single profile and reference them from your models.

Catalog Backend Status
local Local filesystem Usable
iceberg with SQLite Iceberg + SQLite metastore Usable
iceberg with REST + Databricks Iceberg REST API (Unity Catalog) Experimental
iceberg with other backends Any pyiceberg-supported backend Experimental
azure Azure Blob Storage / ADLS Gen2 Experimental
databricks Unity Catalog REST API + credential vending Experimental

Quick start

See the Getting started guide.

A minimal profiles.yml for local development is:

my_project:
  target: dev
  outputs:
    dev:
      type: polars
      schema: dev

      catalog_type: local
      root: ./data

Documentation

Metadata

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