prefect-dbt
Prefect integrations for working with dbt
What it is and what it does
prefect-dbt is a Prefect integration that bridges dbt (data build tool) and Prefect's workflow orchestration platform. It provides tasks and utilities to execute dbt commands—such as dbt run, dbt test, and dbt build—as part of larger Prefect data pipelines. This lets you orchestrate dbt model runs alongside other data tasks, apply Prefect's scheduling, retry logic, and monitoring to dbt workflows, and integrate dbt outputs into downstream pipeline steps.
The package depends on prefect, dbt-core, prefect_shell, and sgqlc. It supports Python 3.10 through 3.13 and is actively maintained. Installation is straightforward with low friction, and the permissive Apache 2.0 license poses no restrictions for most use cases.
Use it for:
- Schedule and monitor dbt model runs as part of a larger Prefect data orchestration pipeline
- Chain dbt transformations with upstream data ingestion and downstream analytics tasks in a single workflow
- Apply Prefect's retry policies, error handling, and alerting to dbt command execution
- Parameterize dbt runs within Prefect flows to test different model configurations or data subsets
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Prefect integration that orchestrates dbt workflows, allowing you to run dbt commands and tasks as part of Prefect data pipelines.
Yes, if you use both Prefect and dbt. The integration is actively maintained, has low install friction, carries no license restrictions, and solves a clear orchestration gap. Install it only if you need to run dbt within Prefect workflows; standalone dbt projects do not require it.
Install
prefect-dbt on PyPI
pip
pip install prefect-dbtuv
uv add prefect-dbtpoetry
poetry add prefect-dbtInstalling prefect-dbt
Before you install
Low install friction with a pure Python wheel. Actively maintained with recent releases; the repository is active and well-starred, indicating ongoing support and community engagement.
License in practice
Apache License 2.0 is permissive, allowing commercial use, modification, and distribution with minimal restrictions—suitable for most production environments.
Quickstart
pip install prefect-dbt
from prefect_dbt.cli.commands import dbt_shell_command
result = dbt_shell_command(command="dbt run")
Requires Python 3.10 or later; dbt-core must be installed separately as a runtime dependency.
Verify before relying
- Whether prefect_shell is a required or optional runtime dependency for typical workflows
- What sgqlc is used for within the integration and whether it is required for all use cases
Package facts
| License | Apache License 2.0 (permissive) |
| Python support | supports the current Python release (>=3.10) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 4 — prefect, dbt-core, prefect_shell, sgqlc |
| Maintenance | actively maintained — 70 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 758,869/month — #5,131 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: prefect_dbt-0.7.25-py3-none-any.whl
Keywords: prefect
Tags
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