Book Image

SQL Server 2017 Developer???s Guide

Book Image

SQL Server 2017 Developer???s Guide

Overview of this book

Microsoft SQL Server 2017 is a milestone in Microsoft's data platform timeline, as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. This book prepares you for advanced topics by starting with a quick introduction to SQL Server 2017's new features. Then, it introduces you to enhancements in the Transact-SQL language and new database engine capabilities before switching to a different technology: JSON support. You will take a look at the security enhancements and temporal tables. Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Toward the end of the book, you'll be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. You'll also learn to integrate Python code into SQL Server and graph database implementations as well as the deployment options on Linux and SQL Server in containers for development and testing. By the end of this book, you will be armed to design efficient, high-performance database applications without any hassle.
Table of Contents (25 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Free Chapter
1
Introduction to SQL Server 2017
Index

Summary


In this chapter, you have learned about SQL Server security. You have learned about principals and securables. When designing a database, you should carefully implement schemas. You give object and statement permissions to database users. To enhance data protection, SQL Server implements encryption in many different ways. The new SQL Server 2016 and 2017 Always Encrypted feature might be extremely useful because you don't need to change existing applications (except for the connection string) to use it. You can filter the rows the users can see and modify these with the help of programmable objects or SQL Server 2016 predicate-based Row-Level Security. Finally, in SQL Server 2016 and 2017, you can also mask data with dynamic data masking for non-privileged users.

In the next chapter, you will learn how to use Query Store to keep your execution plans optimal.