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Now that you know how to create an Azure SQL database, how to connect to it, and how to restore a sample database, it’s now time to start to see what Azure SQL offers to a modern developer.

After having discussed the foundational aspects of querying and manipulating data, it’s now time to focus on more advanced and development-oriented features that you can use in Azure SQL. If you already took a peek at the chapter content, you may be surprised to find a full section on security. Don’t be. Security is not something that can be added later, like an afterthought, that is a nice to have but not so core. On the contrary, security is important as much as performances and maintainability and must be taken into consideration from the ground up. Therefore, the options Azure SQL offers you to keep your data secure are a must-known for everyone who wants to create a modern application – modern because it is not only scalable and modular, but because it is also secure.

When people imagine a table, in most of the cases, this looks like an Excel spreadsheet. There are a bunch of cells organized in rows and columns, and there is usually one column that contains the identifiers of the rows. Azure SQL enables you to use much more than a plain table. You can configure and optimize your table for some specific query patterns, complex analytics, or highly concurrent updates. You can also configure your tables to keep a full history of changes, implement some parts of domain data-integrity logic, and apply fine-grained security rules. In this chapter, you can find some practical advice that can help you leverage the features that Azure SQL provides to create a table that is best fit for your needs.

Azure SQL is not a traditional relational database platform. Every modern database must enable you to use various data formats for different scenarios. Although traditional normalized relational format is battle-tested and proven as optimal technology for a wide range of different scenarios, in some cases, you might find that some other formats might be the better fit for the problem that you are solving.

The advent of cloud computing has brought a lot of innovation in all fields, and relational databases have been taking advantage of that innovation too. They evolved up to the point that many of them, Azure SQL included, now incorporate features that have traditionally been found in non-relational databases, distributed systems, and analytical platforms. Such evolution provides a great number of options in terms of flexibility and scalability, and yet still offers all the consistency and the guarantees provided by the solid mathematical foundations of relational algebra, so that a developer can have the best of both worlds: well-established technologies along with new and disruptive ideas in just one place.

DevOps is a discipline that brings together people, processes, and products to enable continuous delivery of value to end users. It does so by helping to bridge the gap between development, operations, and management. From a developer standpoint, probably the most important aspect of the DevOps discipline is the focus on having a healthy CI/CD pipeline. Continuous Integration (CI) and Continuous Deployment (CD) are two processes that help to support development agility while assuring product quality and stability.

The first mention of Azure SQL, referred to as “Microsoft SQL Services” at the time, was when Microsoft announced “Project Red Dog” (Microsoft Azure) at Microsoft’s Professional Developer Conference (PDC) in 2008. This cloud-hosted version of SQL Server was one of the first services available on Azure. From the beginning, it was meant to provide a Platform as a Service (PaaS) offering of SQL Server, where you don’t have to provision hardware or patch software and you can enjoy benefits that come with running in the cloud – availability, performance, security, and scale – without deploying complex and expensive systems on premises. Since then, Azure SQL has continued to grow and evolve with the Azure platform. As you read this book, it’s important to remember that things are always changing. While some of the “little rocks” or details throughout the book may change slightly as the platform evolves, the “big rocks” you will learn in this book will provide a solid foundation for you to grow in the space of developing with databases.

In the previous chapter, we learned about the Hobits (HoBT, Heap or B-Tree) – classic tables and indexes that are the most common objects in relational databases. In this chapter, you will learn about some special types of tables and indexes that can help you to build better designs for certainscenarios.

Once you have created and configured a database instance, your next task will be to connect a newly developed or existing application to it and start executing data manipulation or retrieval commands.

Azure SQL and its underlying SQL Server query engine are well known in the industry for the low administrative barrier generally required for applications to get good performance and reliability on most conditions with different data sizes and shapes. That said, it is important for application developers to understand the foundations and internals of how query processing works in Azure SQL and what tools and capabilities are available to monitor and troubleshoot performance on both development and production phases.