dbt-snowflake

What it is and what it does

dbt-snowflake is the official adapter that connects dbt to Snowflake, allowing data analysts and engineers to write SQL and YAML-based transformations that run directly in Snowflake. It bridges dbt's modeling and testing framework with Snowflake's cloud data warehouse, enabling version control, testing, documentation, and CI/CD workflows for data pipelines.

The package depends on dbt-core for the transformation engine, dbt-adapters and dbt-common for adapter infrastructure, snowflake-connector-python for Snowflake connectivity, and utility libraries (agate, certifi). It supports Python 3.10, 3.11, 3.12, and 3.13 on macOS, Windows, and Linux, and is classified as production-stable. With no known security vulnerabilities and active maintenance (latest release 2026-07-16), it is a mature choice for teams building analytics workflows on Snowflake.

Use it for:

• Build and test SQL transformation models in Snowflake using dbt's YAML configuration and testing framework.
• Organize raw warehouse data into clean, documented analytics-ready tables with version control and lineage tracking.
• Implement CI/CD pipelines for data transformations, running tests and documentation generation on every commit.
• Denormalize and aggregate raw data into dimensional or fact tables for downstream BI tools and reporting.
• Collaborate on data modeling across teams using dbt's documentation, DAG visualization, and code review workflows.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

dbt-snowflake is the Snowflake adapter for dbt, enabling data transformation and analytics workflows in Snowflake using dbt's SQL and YAML-based modeling framework.

Yes. dbt-snowflake is a production-stable, actively maintained adapter with low install friction and no known vulnerabilities. Install it if you are using Snowflake and want to adopt dbt's SQL-based transformation and testing framework. It is the standard tool for this use case and carries minimal risk.

Install

dbt-snowflake on PyPI

pip install dbt-snowflake

uv add dbt-snowflake

poetry add dbt-snowflake

Installing dbt-snowflake

Before you install

Low install friction with a pure-Python wheel distribution. Actively maintained with a release 29 days old and recent commits; depends on dbt-core, dbt-adapters, dbt-common, snowflake-connector-python, and standard utilities (agate, certifi).

License in practice

Licensed under Apache Software License (permissive), allowing commercial and private use with minimal restrictions.

Quickstart

pip install dbt-snowflake

In your dbt project's profiles.yml:
my_snowflake_db:
  target: dev
  outputs:
    dev:
      type: snowflake
      account: [account_id]
      user: [username]
      password: [password]
      database: [database_name]
      schema: [schema_name]
      warehouse: [warehouse_name]

Then run: dbt run

Requires Python 3.10 or later; Snowflake account credentials and warehouse configuration must be set in profiles.yml before running dbt commands.

Verify before relying

• Whether the package includes built-in support for specific Snowflake features (e.g., dynamic tables, iceberg tables, or Snowflake-specific optimizations).
• Performance characteristics or scaling limits when working with very large datasets in Snowflake.
• Recommended thread pool sizing and concurrency tuning for different warehouse sizes.

Package facts

Evidence: dbt_snowflake-1.12.0-py3-none-any.whl

Keywords: adapter, adapters, database, dbt, dbt Cloud, dbt Core, dbt Labs, dbt-core, elt, snowflake

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