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DATA PLUMBING WITHOUT THE

Open-source data pipeline tool for transforming and integrating data.
Open-source data pipeline tool for
transforming and integrating data.
Open-source data pipeline tool for
transforming and integrating data.



The modern replacement for Airflow.



Start building

Try live tool

The modern
replacement for Airflow




Open-source data pipeline tool for transforming and integrating data.



Watch 2 min demo



Watch 2 min demo




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.

Start building 


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.

Start building 




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.

Start previewing 


PREVIEW



Are you wasting time trying to test your DAGs in production? Get instant
feedback every time you run code in development.

Start previewing 




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.

Deploy pipelines 


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.

Deploy 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.


GIVE YOUR DATA TEAM


MAGICAL POWERS



Start building

Try live tool

Watch 2 min demo

Questions & Answers



Who is the ideal user for this tool?



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.

How difficult is Mage to setup?



You can quickly and easily get started by installing Mage using Docker
(recommended), pip, or conda. Click here for details.

How much does Mage cost?



Mage is free as long as you are self-hosted (AWS, GCP, Azure, or Digital Ocean).

How is Mage’s data pipeline engine software different from Airflow, etc?



Mage differentiates itself from Airflow and other tools based on 4 core design
principles:

 1. Focus on providing the easiest developer experience.

 2. Ensuring engineering best practices are built-into every aspect of data
    pipeline building.

 3. Everything in Mage is about data, that’s why data is a first-class citizen
    in Mage.

 4. Scaling is made simple and possible without overhead of a large dedicated
    infra or DevOps team.

What languages does Mage support?



We currently support SQL, Python, R, and PySpark.

Does Mage integrate with Spark?



Yes! Click here for a step-by-step tutorial to use Mage with Spark on EMR.

How can I contribute or request features?



We love and welcome community contributions! Here is a doc to get you started.



To request features, add a “Feature request” using the New issue button in
Github from this link, or join our feature-request Slack channel.

GET STARTED



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Get instant help

COMMUNITY



GitHub

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Mage AI



Magical powers for data teams

Mage AI



Magical powers for data teams

Mage AI



Magical powers for data teams

Mage AI



Magical powers for data teams

GET STARTED



Documentation

Demo video

Try live tool

Get instant help

COMMUNITY



GitHub

Slack

LinkedIn

Twitter

LEARN



Blog

Tutorials

Contact us

Careers


©
 2024 Mage Technologies, Inc.

Privacy policy

Terms of service

Security

SOC 2

©
 2024 Mage Technologies, Inc.

Privacy policy

Security

SOC 2