Mage is a data pipeline tool that allows data teams to effortlessly integrate and synchronize data from 3rd party sources. It offers real-time and batch pipelines for data transformation using Python, SQL, and R. With Mage, users can run, monitor, and orchestrate thousands of pipelines easily. It provides an easy developer experience, supports multiple programming languages, and incorporates engineering best practices. Mage also offers features like interactive code preview, data versioning and cataloging, collaborative development on cloud resources, and built-in monitoring and observability. It has received positive feedback from users and is expected to be a strong contender in the data pipeline tooling space.
Mage
Data plumbing without the
Watch a quick demo on how to use Mage
Give your data team magical powers
Effortlessly integrate and synchronize data from 3rd party sources.
Build real-time and batch pipelines to transform data using Python, SQL, and R.
Run, monitor, and orchestrate thousands of pipelines without losing sleep.
Build
Have you met anyone who said they loved developing in Airflow? That’s why we designed an easy developer experience that you’ll enjoy.
Easy developer experience
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.
Interactive code
Immediately see results from your code’s output with an interactive notebook UI.
Data is a first-class citizen
Each block of code in your pipeline produces data that can be versioned, partitioned, and catalogued for future use.
Collaborate on cloud
Develop collaboratively on cloud resources, version control with Git, and test pipelines without waiting for an available shared staging environment.
Launch
Don’t have a large team dedicated to Airflow? Mage makes it easy for a single developer to scale up and manage thousands of pipelines.
Fast deploy
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.
Ian Yu
Machine Learning Engineer @ GroupBy Inc.
magical powers
Questions & Answers