Azure SQL – Row Level Security Now Available

Revolutionize Your Business With Generative AI

From product design and software development to virtual agents, content creation, and reporting, GenAI is transforming business. Our AI experts help you unlock GenAI’s full potential and drive growth.

Let’s Get Started

Row-Level Security (RLS) for Azure SQL Database is now generally available. RLS simplifies the design and coding of security in your application. RLS enables you to implement restrictions on data row access. For example ensuring that workers can access only those data rows that are pertinent to their department, or restricting a customer’s data access to only the data relevant to their company.
The access restriction logic is located in the database tier rather than away from the data in another application tier. The database system applies the access restrictions every time that data access is attempted from any tier. This makes your security system more reliable and robust by reducing the surface area of your security system.
Row-level filtering of data selected from a table is enacted through a security predicate filter defined as an inline table valued function. The function is then invoked and enforced by a security policy. The policy can restrict the rows that may be viewed (a filter predicate), but does not restrict the rows that can be inserted or updated from a table (a blocking predicate). There is no indication to the application that rows have been filtered from the result set; if all rows are filtered, then a null set will be returned.
Filter predicates are applied while reading data from the base table, and it affects all get operations: SELECT, DELETE(i.e. user cannot delete rows that are filtered), and UPDATE (i.e. user cannot update rows that are filtered, although it is possible to update rows in such way that they will be subsequently filtered). Blocking predicates are not available in this version of RLS, but equivalent functionality (i.e. user cannot INSERT or UPDATE rows such that they will subsequently be filtered) can be implemented using check constraints or triggers.
This functionality will also be released with SQL Server 2016. If you have Azure though, you get the features now. Another great reason to consider the Microsoft Cloud – you don’t have to wait for a server release to get new functionality! Contact us at Perficient and one of our 28 certified Azure consultants can help plan your Azure deployment today!