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


This chapter explored JSON support in SQL Server 2017. It is not as robust and deep as  XML—there is no native data type, and no optimized storage, and therefore you cannot create JSON indexes to improve performance. Thus, we are talking about built-in and not native JSON support.

However, even with built-in support, it is easy and handy to integrate JSON data in SQL Server. For most of JSON data processing, it would be acceptable. For large JSON documents stored in large database tables, it would be more appropriate to use DocumentDB or other NoSQL based solutions.

In this chapter, you learned that SQL Server 2017 brings built-in support for JSON data; unlike XML, there is no native data type. You used theFOR JSONextension to generate JSON from data in a tabular format and converted JSON data into a tabular format by using theOPENJSONrowset function. You learned how to parse, query, and modify JSON data with a function and how to improve the performance of JSON data processing by...