Google, Databricks, Fivetran, Redis and others launch the Data Cloud Alliance

There’s a new alliance in town: the Data Cloud Alliance. Founded by Google Cloud, Accenture, Confluent, Databricks, Dataiku, Deloitte, Elastic, Fivetran, MongoDB, Neo4j, Redis and Starburst, the group’s mission is to “make data more portable and accessible across disparate business systems, platforms, and environments—with a goal of ensuring that access to data is never a barrier to digital transformation.”

Snowflake filed a trademark registration for “Data Cloud Alliance” in 2020, but that registration is now abandoned and the company isn’t part of this new alliance.

The idea here is to make life easier for the members’ customers by working together to provide APIs and integration support to allow for data portability and accessibility between their platforms, no matter whether those are being used on-premises, or on private or public clouds (or a mix of them). The members will also work together to create “new, common industry data models, processes, and platform integrations to increase data portability and reduce complexity associated with data governance and global compliance,” Google notes in its announcement today. Databricks, for example, says it is excited to partner with Google to “foster data sharing based on open standards like [Databrick’s] Delta Lake.”

It’s worth noting that the partners here are mostly not competitors but offer services that complement each other. Many of these companies have also partnered with Google before, with Confluent, Elastic, MongoDB, Neo4j and Redis Labs working with Google to integrate their services with the Google Cloud Platform, for example.

“Data is the common foundation for all digital transformations,” said Gerrit Kazmaier, VP and GM of Databases, Data Analytics and Business Intelligence at Google Cloud. “By committing to open data standards, access, and integration between the most popular data platforms and applications today, we believe we can significantly accelerate business transformations and close the data to value gap.”