Mage vs. Airbyte

First published on December 13, 2022

 

8 minute read

Thomas Chung

Growth

TLDR

Mage is an open-source data pipeline tool for transforming and integrating data. Find out how Mage compares to open-source ELT alternatives like Airbyte. We’ll break down the features, pricing, pros, cons, and more.

Outline

  • About the products

  • Feature comparison

  • Next steps

⁠About the products

Mage

Mage

is an open-source data pipeline tool for integrating (EL) and transforming (T) data. Mage was started in 2020 by engineers who worked on data and dev tools (e.g.

Airflow

) at Airbnb for 5+ years. Their focus is to provide easy developer experience for building and managing data pipelines.

Airbyte

Airbyte

is an open-source ELT tool, created in July 2020. Their goal is to commoditize data integration by addressing the long tail of connectors through their growing contributor community. They released a cloud offer in April 2022 with a new pricing model distinguishing database from APIs and files.

Feature comparison

Mage

Airbyte

Specialty

Data pipelines

ELT as a first step

Number of sources

307 (from Singer taps and targets)

More than 200

Number of destinations

20 - all the main ones and more (from Singer taps and targets)

All data warehouses, lakes, and databases

Customizations

Mage uses the data engineering community standard for data integrations called the Singer Specification. All connectors are written in Python.

⁠Mage provides tutorials, guides, examples, and training to create custom connectors.

User can edit any pre-built connectors and build new ones within 30 minutes with Airbyte’s Connector Development Kit.

Database replication

Full table and incremental via CDC (change data capture)

Full table and incremental via CDC (change data capture).

Integration with modern data stack

Integrate with any Python library.

⁠Mage has a native integration with DBT: preview DBT results, orchestrate DBT model runs, schedule DBT models to depend on non-DBT tasks (e.g. ETL/ELT pipelines).

Integrate with Kubernetes, Airflow, Prefect, Dagster, and DBT.

Integrations can be contributed by the community.

Support and developer documentation

Support is instantly provided through Slack (

https://www.mage.ai/chat

) and via email (

eng@mage.ai

)

1-on-1 tech support is provided over Zoom and can easily be schedule through Slack and email

Documention (

https://docs.mage.ai

) has been praised by data engineering community

Airbyte provides in-app chat support with an average time to respond of 5 minutes.

Their documentation is comprehensive and full of tutorials. Airbyte also has a Slack and Discourse community where help is available from the Airbyte team, other users or contributors.

Airbyte does not provide any training services.

Support service-level agreements (SLA)

Mage is self-hosted.

Dedicated engineering support available upon request.

Available

Security

SOC2

SOC2, ISO 27001, GDPR

Vendor lock-in

Mage is open-source. The code and connectors you use and write are always yours and available to you if you switch tools.

Mage's technical design makes your code and connectors modular and interoperable.

Airbyte Core and Connectors are open-source

Pricing

Free (self-hosted on AWS, GCP, Azure, or Digital Ocean)

Free (open-source) plan and volume-based pricing differentiating APIs from databases. Credits are rolled over.

Specialty

Mage focuses on data pipelines while Airbyte focuses on ELT as a first step.

Number of sources

Mage currently offers 307 data source connectors while Airbyte provides 200+.

Number of destinations

With Mage, you can add all the main destinations and add additional destinations from an extensive collection of Singer taps and targets.

With Airbyte, you can add all data warehouses, lakes, and databases.

Customizations

Mage uses the data engineering community standard for data integrations called the Singer Specification. All connectors are written in Python. Mage also provides tutorials, guides, examples, and training to create custom connectors.

With Airbyte, users can edit any pre-built connectors and brand new ones within 30 minutes with Airbyte's Connector Development Kit.

Database replication

You can replicate full table and incremental via CDC (change data capture) for both Mage and Airbyte.

Integration with modern data stack

With Mage, you can integrate with any Python library. Mage has a native integration with DBT:

  • Preview DBT results

  • Orchestrate DBT model runs

  • Schedule DBT models to depend on non-DBT tasks (e.g. ETL/ELT pipelines)

Airbyte integrates with Kubernetes, Airflow, Prefect, Dagster, and DBT.

Support and developer documentation

Mage provides instant, real-time support via Slack (

https://www.mage.ai/chat

) and via email (

eng@mage.ai

). Mage also provides 1-on-1 tech support or group training services over zoom which can be easily scheduled through Slack or email. Last but not least, Mage offers rich and detailed documentation (

https://docs.mage.ai

) with frequent updates, including migration support and example tutorials. It has been praised by the engineering community.

Airbyte provides in-app chat support (with average time to respond of 5 minutes). Their documentation is comprehensive and full of tutorials. Airbyte also has a Slack and Discourse community where help is available from the Airbyte team, other users, or contributors. Airbyte does not provide any training services.

Support service-level agreements (SLA)

Both have SLAs available, while Mage is self-hosted. Mage also offered dedicated engineering support available upon requeset.

Security

Both are SOC 2 compliant, while Airbyte is also ISO 27001 and GDPR compliant.

Vendor lock-in

Mage is open-source. The code and connectors you use and write are always yours and available to you if you switch tools. Mage's techincal design makes your code connectors modular and interoperable.

Airbyte Core and Connectors are open-source.

Pricing

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

Airbyte offers both a free (open-source) plan as well as premium plans which is volume-based pricing differentiating APIs from databases. Credits are rolled over.

Conclusion

Airbyte is distinguished by its priorities to support as many data source and destination systems as possible. This is done by using an open-source model for its connectors and actively encouraging its community to contribute.

Mage provides a unique and flexible approach to data transformation that includes orchestration. It was created to incorporate core design principles of easy developer experience, built-in engineering best practices, data as a first-class citizen, and scaling made simple.

Next steps

Want to learn more? Check out the

documentation

.

Want a demo from a real human?

Schedule a 15 minute Zoom

call with our team.

Want to chat? Join our

Slack community

.