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


Stretch DB allows the moving of historical or less frequently needed data dynamically and transparently to Microsoft Azure. Data is always available and online, and you don't need to change queries in your solutions; SQL Server takes care of the location of data and combines retrieving data from the local server and remote Azure location. Therefore, you can completely delegate your cold data to Azure and reduce storage, maintenance, and implementation costs of an on-premises solution for cold data storage and availability. However, there are many limitations to using Stretch DB and most OLTP tables cannot be stretched to the cloud—at least not without schema and constraint changes. Stretch Database brings maximum benefits to tables with historical data that is rarely used. You can calculate the price for data storage and querying against the Azure database and decide whether you would benefit from using the Stretch DB feature.

In the next chapter, you will learn about temporal data...