This release is a pre-release and may not be stable for production use.
trellis Data
trellis is a lightweight, local-first app that connects conceptual and logical data modeling with how you actually build the warehouse today—dbt-core first, with a live canvas that stays aligned to your project.
Why trellis
Typical pain
- ERDs live in separate tools and go stale on real projects.
- Transformations drift from the story the business understands.
- Stakeholders can’t see structure without wading through SQL and YAML.
- “All-in-one” warehouse designers rarely meet teams where they are (dbt, git, the modern stack).
What you get with trellis
- Small PyPI install, local web app — run it beside your dbt project; the canvas and model files (
data_model.yml, dbt YAML) stay in version control, so names, relationships, and descriptions evolve like the rest of your code—not a one-off diagram export. - One place to see entities, fields, relationships, and descriptions—tied to your repo, not a dead export.
- Conceptual view for names and meaning; Logical view for columns, types, and materialization detail—switch without losing context.
- Greenfield: sketch entities and attributes, then push structured artifacts into dbt.
- Brownfield: load what you already modeled in dbt, infer links from relationship tests, and push descriptions and tags back into the project.
What you can do
- Visualize your data model — canvas layout, conceptual vs logical views, less manual “diagram maintenance.”
- Work with your dbt project — point at
manifest.json/catalog.json, keep the diagram honest, round-trip descriptions and tags, and generate relationship tests from drawn links. - Optional — Kimball-style modeling — classify facts and dimensions, sensible default placement, and a Bus Matrix when your team thinks in stars/snowflakes; you can stay on plain entities if you prefer.
- Optional — business events & processes — capture events with 7W-style annotations and group them into processes; most useful for greenfield and dimensional workflows. Skip this entirely if it’s not your methodology.
Getting started
Install
pip install trellis-datamodel
# or: uv pip install trellis-datamodel
Run next to your dbt project
cd /path/to/your/dbt-projecttrellis init— createstrellis.yml(point it at your dbt paths and artifacts).trellis run— opens http://localhost:8089 (usetrellis run --helpfor port and config path).
Generate manifest.json and catalog.json with dbt docs generate in your dbt project so trellis can load models; without them, the UI may start but show no dbt-backed entities.
Install from source or hack on the app: see CONTRIBUTING.md.
Examples & walkthroughs
Short video walkthroughs:
| Getting started | Init, settings in the UI, conceptual vs logical, relationships, push to dbt. |
| dbt integration | Link a project, mock data, bind entities to models, stay in sync with artifacts. |
| Documenting business processes | Optional / experimental: events, 7Ws, processes—enable in config or UI first. |
More narrative walkthroughs and context: full tutorial · general information.
Configuration
After trellis init, edit trellis.yml. Annotated options and defaults live in trellis.yml.example (paths, modeling style, optional lineage/exposures, entity guidance, prefixes, etc.).
You can also open /config in the app to edit settings in the browser (validated saves; see example file for field meanings).
Vision
trellis is built and tested around dbt-core today. The longer-term idea is to stay tool-agnostic—concepts outlive any one framework. Possible directions include dbt Fusion, Pydantic-flavored exports, or adapters for tools like SQLMesh or Bruin where it makes sense. For now, the focus is a great experience with dbt-core.
Contributing
Contributions welcome. Workflow, local dev, tests, and packaging: CONTRIBUTING.md. All contributors sign the CLA once per GitHub account—see CLA.md and the bot on your PR.
Acknowledgments
- dbt-colibri for lineage-related capabilities that support trellis visualization.
License
trellis Datamodel is licensed under the GNU Affero General Public License v3.0. See NOTICE for a short summary of copyright and licensing.
1 maintainer
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