Mage Pro reimagines dbt workflows by embedding dbt model orchestration directly into flexible, modern pipelines. Manage, schedule, and monitor dbt models alongside Python, SQL, and R blocks—all within a single, cohesive project.

No need to maintain separate orchestration tools like Airflow or split workloads across platforms like dbt Cloud. Mage Pro lets both analytics and data engineers collaborate across languages, data tools, and multiple dbt projects—turning fragmented workflows into unified, scalable data pipelines.

With dynamic scheduling, real-time SQL previews, automated dbt testing, and full observability, Mage Pro transforms dbt from a standalone tool into an integrated engine of your production data ecosystem.

How it works

Run and manage dbt models natively:

Execute dbt models individually, as groups, or all at once—while automatically handling model dependencies.

Mix and match dbt models with other blocks:

Combine dbt model runs with Python blocks, R blocks, and SQL blocks inside the same Mage pipeline. No need to silo workflows anymore.

Cross-dbt project orchestration:

Manage and orchestrate dbt models across multiple dbt projects inside a single Mage project. Trigger models from different dbt repositories or configurations in one unified flow.

Dynamic variable injection:

Use flexible runtime variables like env_var, variables, and mage_secret_var to build highly dynamic dbt pipelines that adapt to environments, users, or execution contexts.

Schedule dbt model runs:

Trigger dbt runs on a schedule, from an external event, or through API calls—all natively inside Mage.

Inline SQL model preview:

Instantly preview and validate dbt model outputs as you develop, improving speed and reducing errors.

Automated dbt tests:

Automatically run dbt tests after every pipeline execution. Pipelines fail if any dbt test fails—ensuring data quality by default.

Full observability and alerting:

Monitor dbt model runs, receive real-time alerts on failures, and visualize execution flows with detailed telemetry.

Broad dbt connector support:

Compatible with dbt-bigquery, dbt-snowflake, dbt-redshift, dbt-postgres, dbt-mysql, dbt-spark, dbt-trino, dbt-duckdb, and more.

Why it matters

Modern data teams need orchestration that’s flexible, scalable, and unified across languages and tools—not stitched together by hand. Mage Pro’s dbt integration delivers:

• End-to-end pipelines combining dbt, Python, SQL, and R workflows

• Management of multiple dbt projects under a single control plane

• Full dynamic scheduling, monitoring, and alerting—no external orchestrators needed

• Faster development, safer deployments, and simplified infrastructure

Mage Pro transforms dbt into a core part of your broader data architecture—letting you ship faster, fix easier, and scale smarter.

Learn more