dbt-colibri
A column lineage parser and dashboarding tool
Decision gist · record as of 2026-08-14
Yes. Low install friction, no security vulnerabilities, permissive MIT license, and active maintenance make this a straightforward choice for dbt users needing column-level lineage visibility. The self-hosted, static-HTML approach eliminates vendor lock-in concerns. Install if your team uses dbt and wants transparent, flexible lineage tracking.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires dbt artifacts (manifest.json and catalog.json) generated by running dbt compile and dbt docs generate first.
- Low friction install with only two runtime dependencies (click and sqlglot).
- Actively maintained with a recent release, supporting Python 3.9 through 3.13.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal obligations—suitable for commercial and private projects.
last release 2026-06-03 (72 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 90,255 downloads/mo, #13,606 on PyPI
Alternatives
Verify before relying
pip install dbt-colibri
# After running: dbt compile && dbt docs generate
colibri generate
# Opens dist/index.html in browser- Whether the tool handles all dbt model types equally or has limitations beyond the noted Databricks SQL-only constraint.
- Performance characteristics and HTML file size for projects with thousands of models or columns.
What it is and what it does
dbt-colibri is a lightweight CLI tool that parses dbt project artifacts to extract column-level lineage—the path each column takes through your dbt transformations—and renders it as an interactive, self-contained HTML dashboard. It uses SQLGlot to parse SQL and extract column dependencies, then combines that with dbt's manifest and catalog metadata to build a complete lineage graph. The tool generates a static HTML file that requires no external services, cloud dependencies, or complex setup.
You run it after your normal dbt compile and dbt docs generate steps, point it at your target directory, and get back a browsable visualization of how data flows column-by-column through your models. It's designed for data teams who need transparency into their transformation logic without vendor lock-in or enterprise tooling overhead. The package supports a wide range of dbt adapters (Snowflake, BigQuery, Redshift, duckDB, Postgres, Databricks, Athena, Trino, SQL Server, ClickHouse, Oracle, StarRocks) and has been tested against dbt-core 1.8.x through 1.10.x.
Use it for
- Generate column lineage reports for dbt projects to understand data dependencies before refactoring models.
- Deploy lineage dashboards to GitHub Pages or internal web servers via CI/CD for team visibility.
- Audit data quality by tracing which source columns feed into critical downstream tables.
- Document dbt project structure for onboarding new team members without manual diagram creation.
- Identify unused columns or dead-end transformations by visualizing the complete column flow.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Low install friction, no security vulnerabilities, permissive MIT license, and active maintenance make this a straightforward choice for dbt users needing column-level lineage visibility. The self-hosted, static-HTML approach eliminates vendor lock-in concerns. Install if your team uses dbt and wants transparent, flexible lineage tracking.
Install
dbt-colibri on PyPI
Before you install
Low friction install with only two runtime dependencies (click and sqlglot). Actively maintained with a recent release, supporting Python 3.9 through 3.13.
Requires dbt artifacts (manifest.json and catalog.json) generated by running dbt compile and dbt docs generate first.
License in practice
MIT license permits unrestricted use, modification, and distribution with minimal obligations—suitable for commercial and private projects.
Quickstart
pip install dbt-colibri
# After running: dbt compile && dbt docs generate
colibri generate
# Opens dist/index.html in browserVerify before relying
- Whether the tool handles all dbt model types equally or has limitations beyond the noted Databricks SQL-only constraint.
- Performance characteristics and HTML file size for projects with thousands of models or columns.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesclicksqlglot |
| Maintenance | Actively maintained 72 days since the last release |
| First released | |
| Downloads | 90,255 / month, #13,606 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9 |
Evidence: dbt_colibri-0.3.6-py3-none-any.whl
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