Build smarter and efficient database application systems for your organization with SQL Server 2017
- Build database applications by using the development features of SQL Server 2017
- Work with temporal tables to get information stored in a table at any time
- Use adaptive querying to enhance the performance of your queries
Microsoft SQL Server 2017 is the next big step in the data platform history of Microsoft as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. Compared to its predecessor, SQL Server 2017 has evolved into Machine Learning with R services for statistical analysis and Python packages for analytical processing. This book prepares you for more advanced topics by starting with a quick introduction to SQL Server 2017's new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to enhancements in the Transact-SQL language and new database engine capabilities and then switches to a completely new technology inside SQL Server: JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables.
Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Towards 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 in SQL Server and graph database implementations along with deployment options on Linux and SQL Server in containers for development and testing.
By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle.
What you will learn
- Explore the new development features introduced in SQL Server 2017
- Identify opportunities for In-Memory OLTP technology
- Use columnstore indexes to get storage and performance improvements
- Exchange JSON data between applications and SQL Server
- Use the new security features to encrypt or mask the data
- Control the access to the data on the row levels
- Discover the potential of R and Python integration
- Model complex relationships with the graph databases in SQL Server 2017
Who This Book Is For
Database developers and solution architects looking to design efficient database applications using SQL Server 2017 will find this book very useful. In addition, this book will be valuable to advanced analysis practitioners and business intelligence developers. Database consultants dealing with performance tuning will get a lot of useful information from this book as well.
Some basic understanding of database concepts and T-SQL is required to get the best out of this book.
Table of Contents
Chapter 1. Introduction To Sql Server 2017
Chapter 2. Review Of Sql Server Features For Developers
Chapter 3. Sql Server Tools
Chapter 4. Transact-Sql And Database Engine Enhancements
Chapter 5. Json Support In Sql Server
Chapter 6. Stretch Database
Chapter 7. Temporal Tables
Chapter 8. Tightening The Security
Chapter 9. Query Store
Chapter 10. Columnstore Indexes
Chapter 11. Introducing Sql Server In-Memory Oltp
Chapter 12. In-Memory Oltp Improvements In Sql Server 2017
Chapter 13. Supporting R In Sql Server
Chapter 14. Data Exploration And Predictive Modeling With R In Sql Server
Chapter 15. Introducing Python For Sql Server
Chapter 16. Graph Databases
Chapter 17. Sql Server On Linux / In Containers