Rosetta DataBase Transformation Studio is an open-source desktop application that simplifies your data transformation journey with dbt Core™ and brings the power of AI into your analytics engineering workflow.
Whether you're just getting started with dbt Core™ or looking to streamline your transformation logic with AI assistance, DBT Studio offers an intuitive interface to help you build, explore, and maintain your data models efficiently.
- Connect to your data warehouse, assuming your RAW layer is already in place.
- Staging Layer Generator: Automatically create staging models based on RAW tables.
- Enhanced Layer Generator: Build intermediate models to enrich and prepare your data.
- Business Models with AI: Describe the business logic, and let the AI assist you in generating robust business models.
- AI-Generated Analytical Queries: Generate analysis-ready queries and dashboard datasets using natural language.
- Explore your data using an in-app SQL editor with auto-run, formatting, and result preview.
- Use the built-in Git explorer with Select All feature to easily commit and manage project changes.
- Compile, test, run, and document dbt™ projects directly from the UI—no terminal needed.
Leverage AI to:
- Automatically draft dbt™ models from descriptions or table schemas.
- Generate joins, transformations, and aggregations with minimal input.
- Translate business questions into SQL queries for analysis.
DBT Studio includes an integrated Python environment to:
- Install and manage dbt™ without external setup.
- Seamlessly configure and run dbt™ from within the application.
DBT Studio embeds the open-source Rosetta CLI tool to support metadata-driven dbt™ development:
- Model generation aligned with your naming conventions and standards.
- Reusable templates and YAML documentation support.
Get a quick overview of Rosetta DBT Studio in action:
💡 More tutorials and walkthroughs are available on our YouTube Channel.
Download the latest release for your OS from the Releases Page and follow the instructions to get started.
No prior Python or dbt™ installation required.
cd project-dir
npm installStart the app in the dev environment:
npm startTo package apps for the local platform:
npm run packageThe build files after packaging can be found at: /release/build
AGPL-3.0 - See LICENSE for details.