Amazon Redshift announces new fine-grained access control capabilities to nested objects (preview)


Amazon Redshift data lake analytics supports querying nested data in Parquet, ORC, JSON, and Ion file formats. You can now apply AWS Lake Formation FGAC to your nested data, and query with Amazon Redshift data lake analytics. By using DDM in Amazon Redshift, you can protect sensitive data in your data warehouse. you can apply DDM policies to scalar attributes in SUPER data type columns, your SUPER data will be masked based on the masking function defined in masking policies, you can use the full path of SUPER object as input path, and the full path of SUPER object as output path.

Amazon Redshift data lake analytics supports querying nested data in Parquet, ORC, JSON, and Ion file formats. You can now apply Lake Formation fine-grained access control to your nested objects, and query with Amazon Redshift data lake analytics. Using dynamic data masking (DDM) in Amazon Redshift, you can protect sensitive data in your data warehouse. you can apply dynamic data masking policies to scalar attributes in SUPER data type columns, your SUPER data will be masked based on the masking function defined in masking policies, you can use the full path of SUPER object as input path, and the full path of SUPER object as output path. To learn more, visit the Amazon Redshift database developer guide and blog.

The new FGAC capabilities are available as a preview in the following AWS Regions: Asia Pacific (Tokyo), US East (Ohio), US East (N. Virginia), US West (Oregon), Europe (Ireland), Europe (Stockholm). To learn more, visit the Amazon Redshift database developer guide.



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