Here’s a new feature that I like very much: Limiting exposure of sensitive data like user emails, phone numbers, addresses, credit card numbers and so on.
This feature has been available in the Azure SQL Database for a while and now it is included in the new SQL Server 2016 . So let’s see it in action…
My previous post was focused on controlling read operations. With the latest enhancements to the row-level security, it is now possible to restrict write operations as well. This feature is currently available as a preview now generally available in Azure SQL Database V12. Let’s see how that works.
Row-Level Security (RLS) is a new feature of SQL Server 2016 and Azure SQL Database that enables data access control based on the users executing those queries: if a user isn’t authorized to access certain rows in a table then those rows are automatically filtered out by the database engine. This feature promises to simplify design and coding of applications, especially in complex multi-tenancy environments, as the access control logic is moved from the application to the database. In short, instead of writing queries like this:
CREATE VIEW vwInventory AS ... (implements security logic); SELECT * FROM vwInventory WHERE isVisibleTo = 'Paul'
We write simple queries like this:
SELECT * FROM Inventory;
Isn’t that cool?
In the on-premises world, when we install a SQL Server on our own servers, we decide on SQL Version (2012, 2014….), Edition (Standard, Enterprise, Epress…) and we set the database Compatibility Levels according to our applications’ specs. But what is it like with the Azure SQL Database (PaaS)? The answer is – it’s very different so let’s go through the key points to have in mind:
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There are two flavors of SQL Server in Azure: one is the traditional SQL Server platform hosted in Azure virtual machines, also described as Infrastructure as a Service (IaaS). The other is called Azure SQL Database, database-as-a-service or Platform as a Service (PaaS). there are several important differences in functionality and features, so let’s look at them:
