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SQL Server 2017 Developer???s Guide

SQL Server 2017 Developer???s Guide

3.6 (5)
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SQL Server 2017 Developer???s Guide

SQL Server 2017 Developer???s Guide

3.6 (5)

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 (19 chapters)
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1
Introduction to SQL Server 2017

Stretch DB architecture

When you enable Stretch Database for an on-premise SQL Server 2017 database, SQL Server automatically creates a new stretch database in MS Azure SQL Database as an external source and a remote endpoint for the database.

When you query the database, the SQL Server's database engine runs the query against the local or remote database, depending on the data location. Queries against stretch-enabled tables return both local and remote data by default. This is completely transparent to the database user. This means that you can use Stretch Database without changing Transact-SQL code in your queries, procedures, or applications. You can stretch an entire table or a portion of table data. The data migration is done asynchronously and transparently. In addition, Stretch Database ensures that no data is lost if a failure occurs during migration. It also has...

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