What is dbt used for?

dbt is a data transformation framework that lets analysts and engineers build analytics models with software-engineering practices; v2.0 is a ground-up rewrite in Rust. It is a good fit for analytics engineering workflows and speeding up very large dbt projects.

Yes. dbt is open source under the Apache-2.0 licence. Its source code is on GitHub at dbt-labs/dbt and is written mainly in Rust.

Yes. dbt is open source, so the software itself is free to use. A managed cloud version is also available, with paid plans from $100 per seat per month.

What is dbt an alternative to?

dbt is an open-source alternative to Matillion, Coalesce and Keboola. Other open-source alternatives to Matillion include Bruin, Duckle and Airbyte.

Is dbt actively maintained?

Yes. The most recent commit to dbt was on 2 October 2026, and the latest release is v2.0.5, published on 18 September 2026. The project has 14k stars on GitHub.

dbt: open-source alternative to Matillion, Coalesce, Keboola

About dbt

dbt is a framework for transforming data in a warehouse using the same practices that software engineers apply to applications. Analysts and analytics engineers write models, and dbt parses, compiles and runs the project so that transformations are version-controlled and repeatable.

The repository now holds the Apache 2.0 source of dbt v2.0, a ground-up rewrite in Rust. According to its README, v2.0 parses and compiles projects much faster than v1, enforces a stricter language specification at parse time, produces Parquet artifacts alongside the existing JSON ones, and ships as one standalone executable, so no Python installation is needed. The local documentation experience was rebuilt around those artifacts to handle large projects.

The Apache 2.0 code is available to everyone, while the packaged dbt distribution adds dbt-specific customizations under a separate dbt product license. v2.0 supports macOS and Linux on x86-64 and ARM. The v1 Python implementation continues on the 1.latest branch. dbt Labs also offers dbt as a commercial cloud platform.

Key features

Data transformation using software engineering practices
Faster parsing and compiling in v2.0
Strict language specification checks at parse time
Parquet artifacts for querying project metadata
Single binary without a Python runtime
Rebuilt local documentation experience

Good fit for

→Analytics engineering workflows
→Speeding up very large dbt projects

Built with: Rust
Tags: data-transformation; analytics-engineering; elt; sql; data-modeling; rust; business-intelligence; data-warehouse

dbt: questions and answers

What is dbt used for?: dbt is a data transformation framework that lets analysts and engineers build analytics models with software-engineering practices; v2.0 is a ground-up rewrite in Rust. It is a good fit for analytics engineering workflows and speeding up very large dbt projects.
Is dbt open source?: Yes. dbt is open source under the Apache-2.0 licence. Its source code is on GitHub at dbt-labs/dbt and is written mainly in Rust.
Is dbt free?: Yes. dbt is open source, so the software itself is free to use. A managed cloud version is also available, with paid plans from $100 per seat per month.
What is dbt an alternative to?: dbt is an open-source alternative to Matillion, Coalesce and Keboola. Other open-source alternatives to Matillion include Bruin, Duckle and Airbyte.
Is dbt actively maintained?: Yes. The most recent commit to dbt was on 2 October 2026, and the latest release is v2.0.5, published on 18 September 2026. The project has 14k stars on GitHub.