AWS Lambda user-defined functions (UDFs) enable you to use an AWS Lambda function as a UDF in Amazon Redshift and invoke it from Redshift SQL queries. This functionality enables you to write custom extensions for your SQL query to achieve tighter integration with other services or third-party products. You can write Lambda UDFs to enable external tokenization, data masking, identification or de-identification of data by integrating with vendors like Protegrity, and protect or unprotect sensitive data based on a user’s permissions and groups, in query time. With support for dynamic data masking, customers can easily protect their sensitive data and control granular access by managing Data Masking policies. Suppose you have applications that have multiple users and objects with sensitive data that cannot be exposed to all the users. You have requirements to provide a different granular security level that you want to give different groups of users. Redshift Dynamic Data Masking is configurable to allow customers to define consistent, format-preserving, and irreversible masked data values. Once the feature is GA, you begin using it immediately. The security admins can create and apply policies with just a few commands.