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Enterprise Layer Intelligence
Categories/Data Platform & Integration/Mage
Mage

Mage

Founded by Tommy Dang

Build, run, and monitor automated data pipelines using Python and SQL

Pricing model

Free Trial

Rating

★ Positive

Time to value

Immediate

You can use Mage AI to build and operate automated data pipelines with Python and SQL. The tool lets you turn manual tasks into scheduled workflows that extract, transform, and load information across your databases and cloud warehouses. You can automatically validate incoming data to catch errors before dashboards break, and self-healing features help recover failed pipeline runs. It also integrates with tools like dbt and external APIs, allowing your team to clean messy datasets and feed reliable context directly into business dashboards and custom AI agents.

What Mage does

Write and schedule Python data pipelinesRun dbt models alongside SQL queries in a single workflowSet data quality rules to block invalid entriesDiagnose and recover from pipeline run failuresConnect external APIs to cloud data warehousesTrack execution run times and workflow logsSelf-healing workflows that diagnose and repair pipeline run failuresUnified execution for Python, SQL, and dbt modelsBuilt-in automated data validation to stop bad data before productionAI-assisted code generation for pipeline steps and testsCode and execution analysis to remove processing bottlenecksOpen source self-hosting alongside cloud deployment options

Pricing breakdown

Pricing model: Free trial

PlanList price
Starter$29 / mo
Team$100 / mo

Frequently asked

dbtdbtPythonPythonStripeStripeSalesforceSalesforce

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Mage AI, data orchestration, data pipelines, Python pipelines, SQL workflows, dbt, data validation, self-healing pipelines, open source data engineering, data integration, pipeline monitoring, ETL, ELT, data engineering, workflow management