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

Beyond relational


Beyond relational is actually only a marketing term. The relational model, used in the relational database management system, is nowhere limited to specific data types, or specific languages only. However, with the term beyond relational, we typically mean using specialized and complex data types that might include spatial and temporal data, and XML or JSON data, and extending the capabilities of the Transact-SQL language with CLR languages like Visual C#, or statistical languages like R. SQL Server, in versions before 2016, already supports some of the features mentioned. Here is a quick review of this support, which includes:

  • Spatial data
  • CLR support
  • XML data

Spatial data

In modern applications, often you want to show your data on a map, using the physical location. You might also want to show the shape of the objects that your data describes. You can use spatial data for tasks like these. You can represent the objects with points, lines, or polygons. From the simple shapes...