Airbyte and dbt Labs Enhance Partnership to Simplify Data Integration and Transformation

Airbyte, an open-source integration provider, is unveiling its expanded partnership with dbt Labs, an analytics engineering company, accompanied by a new integration to enable dbt Cloud customers to schedule and initiate dbt jobs from within Airbyte Cloud.

“Our companies already share hundreds of users and now they will see the integration of our cloud products, making it simple to use the two together,” said Michel Tricot, co-founder and CEO of Airbyte. “With partners like dbt Labs, we are building a more open, modern data stack to better serve the data community.”

The integration aims to streamline data migration and transformation while mitigating lock-in. Airbyte moves data from a variety of sources as dbt organizes data for analysis; examples of this organization include continuous defining of key business logic or standardizing data structures.

Airbyte’s open-source data integration rectifies manual build and maintenance of data connectors due to a lack of connector support from closed-source ELT (extract, load, and transform) technologies. It also eliminates the need to modify pre-built data connectors in order for it to truly work within your data infrastructure.

dbt Cloud’s centralized development experience propels development processes and encourages collaboration in building and deploying production-grade data pipelines, according to the vendor Accompanied by version control and CI/CD, pre-production testing, documentation of models, modular SQL modeling, and built-in dependency management, dbt Cloud empowers safe deployments, monitoring, and investigation of transformation code in a web-based UI.

“We’re thrilled to deepen this partnership with Airbyte, a company with whom we are aligned regarding the importance of open standards in the data ecosystem,” said Nikhil Kothari, director of technology partnerships at dbt Labs. “This partnership and integration will help better serve our joint users, customers, and the data community as a whole.”

To learn more about this expanded collaboration, please visit or