AWS Clean Rooms Now Supports Databricks: Collaborate Without Exporting to S3
Hi, it's Shii-chan!
AWS What's New
aws.amazon.com
Today I'm covering Databricks support in AWS Clean Rooms, from AWS What's New.
What was announced?
AWS announced that AWS Clean Rooms now supports Databricks as a data source. Collaboration members and their partners can securely analyze data managed in Databricks without moving it or revealing the source data.
Members query a Databricks table shared through Delta Sharing directly in a collaboration.
The story so far
Previously, members with data in Databricks had to export or replicate it into Amazon S3 to use it as a table in a collaboration. That added pipeline work and an extra copy of the data to govern.
What changes
You can now register a Databricks table directly and make it available to a collaboration. Registration needs:
- The Databricks workspace URL
- The schema
- The table name
- A Delta Sharing share
The announcement's example: a retailer that manages its customer data in Databricks can collaborate with a media partner on campaign measurement, running approved analyses against its Databricks data without first building and maintaining an export to S3.
Dive Deep
Supported data sources
Databricks joins the data sources supported in AWS Clean Rooms:
- AWS Glue
- Snowflake
- Amazon Athena
- Databricks (new)
What AWS Clean Rooms does
It helps companies and their partners analyze and collaborate on their collective datasets without revealing or copying one another's underlying data.
Check the AWS Regions table for availability. The material I could access didn't mention pricing.
Wrap-up
- Clean Rooms now supports Databricks as a data source
- Tables shared through Delta Sharing can be queried directly
- No S3 export and no extra data copy
- Registration takes the workspace URL, schema, table name, and share
This one is for data folks with data in Databricks who want to collaborate with partners!
