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Project description
SQLMesh is a next-generation data transformation and modeling framework that is backwards compatible with dbt. It aims to be easy to use, correct, and efficient.
SQLMesh enables data practitioners to efficiently run and deploy data transformations written in SQL or Python.
Although SQLMesh will make your dbt projects more efficient, reliable, and maintainable, it is more than just a dbt alternative.
Select Features
- Semantic Understanding of SQL
- Compile time error checking (for 10 different SQL dialects!)
- Definitions using simply SQL (no need for redundant and confusing Jinja + YAML)
- Self documenting queries using native SQL Comments
- Efficiency
- Never builds a table more than once
- Partition-based incremental models
- Confidence
- Plan / Apply workflow like Terraform to understand potential impact of changes
- Easy to use CI/CD bot
- Automatic column level lineage and data contracts
- Unit tests and audits
For more information, check out the website and documentation.
Getting Started
Install SQLMesh through pypi by running:
pip install sqlmesh
Follow the tutorial to learn how to use SQLMesh.
Join our community
We'd love to join you on your data journey. Connect with us in the following ways:
- Join the Tobiko Slack community to ask questions, or just to say hi!
- File an issue on our GitHub.
- Send us an email at hello@tobikodata.com with your questions or feedback.
Contribution
Contributions in the form of issues or pull requests are greatly appreciated. Read more about how to develop for SQLMesh.
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