Start developing locally with a single command or launch a dev environment in your cloud using Terraform.
Language of choice
Write code in Python, SQL, or R in the same data pipeline for ultimate flexibility.
Engineering best practices built-in
Each step in your pipeline is a standalone file containing modular code that’s reusable and testable with data validations. No more DAGs with spaghetti code.
Preview
Are you wasting time trying to test your DAGs in production? Get instant feedback every time you run code in development.
Deploy Mage to AWS, GCP, Azure, or DigitalOcean with only 2 commands using maintained Terraform templates.
Scaling made simple
Transform very large datasets directly in your data warehouse or through a native integration with Spark.
Fully-featured observability
Operationalize your pipelines with built-in monitoring, alerting, and observability through an intuitive UI.
You’ll love Mage. I bet Airflow gets dethroned by Mage next year!
Zach Wilson
Staff Data Engineer @ Airbnb
Awestruck when I used Mage for the first time. It’s super clean and user-friendly.
Ajith Shetty
Senior Data Engineer @ Miniclip
One thing that hasn't been highlighted much about Mage is the community.
The slack channel has been great and not only did they help me with my immediate problems but they also took a SERIOUS look at my feature requests and included one of them in the latest release!
Jon White
Principal Architect @ Red Alpha
I can say even after just trying it once, Mage would help any Data Engineering team write uniform, clean, well tested Data Pipelines. This is NOT something found in Airflow, Prefect, or Dagster.
Daniel Beach
Senior Data Engineer @ Rippleshot
The go to tool for any team looking to build and orchestrate data pipelines. Very friendly UI with a great developer experience, saving time in development.
Mage is going to be the clear winner in the data pipeline tooling space.
Sujith Kumar
Senior Data Engineer @ ZebPay
I want to thank the Mage team for building such a great product. I am happy and excited to start using Mage as one of our daily data tools.
Juan Mantegazza
Lead Data Engineer @ Zubale
I just loved using it, so easy and intuitive to use.
Petrica Leuca
Freelance Data Engineer
Probably will make people better programmers in general.
Our tool was built with data engineers and data scientists in mind, but is not limited to those roles. Other data professionals could find value in the tool.