Granting access with filters - Amazon DataZone
AWS Glue tablesAmazon Redshift

Granting access with filters

Amazon DataZone enables fine-grained access control by translating the defined row and column filters into appropriate grants for AWS Lake Formation and Amazon Redshift. Below is an explanation of how Amazon DataZone materializes these filters for both AWS Glue tables and Amazon Redshift.

AWS Glue tables

When a subscription to an AWS Glue table with row and/or column filters is approved, Amazon DataZone materializes the subscription by creating grants in AWS Lake Formation with Data Cell Filters, ensuring that the members of the subscriber project are only able to access the rows and columns they are allowed to access based on the filters applied to the subscription.

Amazon DataZone first translates the row and columns filters applied in Amazon DataZone to AWS Lake Formation Data Cell Filters. If multiple row and columns filters are used, Amazon DataZone unions all the columns and all the row filter conditions to compute effective permissions at both row and column level. Amazon DataZone then creates a single AWS Lake Formation data cell filter using effective row and column permissions.

Once the data cell filter is created, Amazon DataZone shares the subscribed table with the subscriber project by creating read-only (SELECT) permissions in AWS Lake Formation using this data cell filter.

Amazon Redshift

When a subscription to an Amazon Redshift table/view with row and/or column filters is approved, Amazon DataZone materializes the subscription by creating scoped-down late binding views in Amazon Redshift, ensuring that the members of the subscriber project are only able to access the rows and columns they are allowed to access based on the row and column filters applied to the subscription.

Amazon DataZone first translates the row and columns filters applied to a subscription in Amazon DataZone to an Amazon Redshift late binding view. If multiple row and columns filters are used, Amazon DataZone unions all the columns and all the row filter conditions from to compute effective permissions at both row and column level. Amazon DataZone then creates the late binding view using effective row and column permissions.

Once the late binding view is created, Amazon DataZone shares this view with the members of subscriber project by creating read-only (SELECT) permissions in Amazon Redshift.