11 Managed SQL with Azure SQL Database

In the last chapter, you learned how to create a scheduled pipeline for processing data in Azure. Azure Data Factory lets you automate the common steps in the analytics processing workflow. In chapter 6, you saw another piece of the processing workflow, with Stream Analytics calculations that flowed into a SQL Server database.

In this chapter, you’ll learn more about the Azure SQL Database (SQLDB). You’ll learn how abstracting the underlying SQL Server allows SQLDB to make complex functionality work with only a few clicks. You’ll create a highly available database, and learn how to balance cost and performance. You’ll work through some of the most common tasks in working with SQLDB. By the end, you’ll have a system ready to support end users with analytic queries in SQL.

11.1  Creating an Azure SQL Database

11.1.1  Create a SQL Server and SQLDB

11.2  Securing SQLDB

11.3  Availability and recovery

11.3.1  Restoring and moving SQLDB

11.3.2  Database safeguards

11.3.3  Creating alerts for SQLDB

11.4  Optimizing cost for SQLDB

11.4.1  Pricing structure

11.4.2  Scaling SQLDB

11.4.3  Serverless

11.4.4  Elastic Pools

11.5  Exercises

11.5.1  Exercise 1

11.5.2  Exercise 2

11.5.3  Exercise 3

11.5.4  Exercise 4

11.6  Summary