dbt integration is currently only supported when using Mage in Docker or in Mage Pro.

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What is Mage’s dbt Integration?

Mage is a modern data pipeline tool that lets you build, schedule, and monitor dbt models alongside your data workflows — all in one platform. With Mage, you can fully automate your dbt workflows without using Airflow or dbt Cloud.

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Who Should Use dbt in Mage?

Mage’s dbt integration is designed for both analytics engineers and data engineers who want more control, flexibility, and observability in their data workflows.

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Analytics engineers

If you’re transforming raw data into clean, analytics-ready datasets using dbt, Mage helps you:

  • A visual interface to build and run dbt models
  • The ability to chain dbt steps with Python or SQL blocks
  • Easy scheduling and triggering for model runs
  • Live SQL previews to speed up development

Mage empowers analytics teams to move faster, test confidently, and collaborate more effectively — all within a unified platform.

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Data engineers

If you’re building and orchestrating production-grade data pipelines, Mage lets you:

  • Run dbt models as part of larger end-to-end workflows
  • Replace complex orchestration tools like Airflow
  • Run dbt across environments — including Docker, Kubernetes, Mage Pro, or in the cloud (AWS, GCP, Azure)
  • Monitor, debug, and get alerts on dbt runs with built-in observability tools

Mage simplifies pipeline orchestration and lets you focus on data logic — not infrastructure setup or maintenance.

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Key Features

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Schedule dbt model runs

Set dbt models to run:

  • On a schedule
  • When a file or event triggers
  • From an API call or upstream task

This is perfect for productionizing your dbt workflows.

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Run specific dbt models and their dependencies

Use Mage’s visual interface to:

  • Select and run individual dbt models
  • Automatically include required dependencies

This saves time during development and debugging.

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Exclude Models When Running All

Need to run everything except one model? No problem. Mage lets you exclude specific dbt models in any run.

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Chain dbt Models with Other Tasks

Build workflows where dbt models run after:

  • Pulling data from APIs
  • Completing a Python or SQL block
  • Finishing a different pipeline

You can treat dbt as a native building block in your DAG.

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Preview dbt model results as you write SQL

Mage lets you preview dbt model output as you write SQL, helping you test and iterate faster without running full pipelines.

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Build dynamic dbt pipelines using flexible variable interpolation

Take advantage of dynamic variable interpolation like:

  • {{ env_var('...') }}
  • {{ variables('...') }}
  • {{ mage_secret_var('...') }}

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Automatically run dbt tests every time a pipeline runs

Mage will:

  • Detect and run your dbt tests during each pipeline run
  • Fail the pipeline if any dbt test fails

This enforces quality without extra setup.

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Built-In Monitoring and Alerting

Mage gives you full observability into your dbt runs:

  • Track model run history
  • See logs and SQL output
  • Get alerts when models fail

You don’t need to wire up additional logging systems.

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Supported connectors

  1. dbt-bigquery
  2. dbt-clickhouse
  3. dbt-core
  4. dbt-dremio
  5. dbt-duckdb
  6. dbt-mysql
  7. dbt-postgres
  8. dbt-redshift
  9. dbt-snowflake
  10. dbt-spark
  11. dbt-sqlserver
  12. dbt-synapse
  13. dbt-trino

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Tutorials

Explore our tutorial to set up and run your first dbt models in Mage: