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SQL Server 2017 Developer???s Guide

You're reading from   SQL Server 2017 Developer???s Guide A professional guide to designing and developing enterprise database applications

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788476195
Length 816 pages
Edition 1st Edition
Languages
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Authors (3):
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Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
Miloš Radivojević Miloš Radivojević
Author Profile Icon Miloš Radivojević
Miloš Radivojević
William Durkin William Durkin
Author Profile Icon William Durkin
William Durkin
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Toc

Table of Contents (19) Chapters Close

Preface 1. Introduction to SQL Server 2017 FREE CHAPTER 2. Review of SQL Server Features for Developers 3. SQL Server Tools 4. Transact-SQL and Database Engine Enhancements 5. JSON Support in SQL Server 6. Stretch Database 7. Temporal Tables 8. Tightening Security 9. Query Store 10. Columnstore Indexes 11. Introducing SQL Server In-Memory OLTP 12. In-Memory OLTP Improvements in SQL Server 2017 13. Supporting R in SQL Server 14. Data Exploration and Predictive Modeling with R 15. Introducing Python 16. Graph Database 17. Containers and SQL on Linux 18. Other Books You May Enjoy

What this book covers

Chapter 1, Introduction to SQL Server 2017, very briefly covers the most important features and enhancements, not just those for developers. The chapter shows the whole picture and point readers in the direction of where things are moving.

Chapter 2, Review of SQL Server Features for Developers, brief recapitulates the features available for developers in previous versions of SQL Server and serves as a foundation for an explanation of the many new features in SQL Server 2016. Some best practices are covered as well.

Chapter 3, SQL Server Tools, helps you understand the changes in the release management of SQL Server tools and explores small and handy enhancements in SQL Server Management Studio (SSMS). It also introduces RStudio IDE, a very popular tool for developing R code, and briefly covers SQL Server Data Tools (SSDT), including the new R Tools for Visual Studio (RTVS), a plugin for Visual Studio, which enables you to develop R code in an IDE that is popular among developers using Microsoft products and languages. The chapter introduces Visual Studio 2017 and shows how it can be used it for data science applications with Python.

Chapter 4, Transact-SQL and Database Engine Enhancements, explores small Transact-SQL enhancements: new functions and syntax extensions, ALTER TABLE improvements for online operations, and new query hints for query tuning.

Chapter 5, JSON Support in SQL Server, explores the JSON support built into SQL Server. This support should make it easier for applications to exchange JSON data with SQL Server.

Chapter 6, Stretch Database, helps you understand how to migrate historical or less frequently/infrequently accessed data transparently and securely to Microsoft Azure using the Stretch Database (Stretch DB) feature.

Chapter 7, Temporal Tables, introduces support for system-versioned temporal tables based on the SQL:2011 standard. We explain how this is implemented in SQL Server and demonstrate some use cases for it (for example, a time-travel application).

Chapter 8, Tightening Security, introduces three new security features. With Always Encrypted, SQL Server finally enables full data encryption. Row-level security on the other hand, restricts which data in a table can be seen by a specific user. Dynamic data masking is a soft feature that limits the exposure of sensitive data by masking it to non-privileged users.

Chapter 9, Query Store, guides you through Query Store and helps you troubleshoot and fix performance problems related to execution plan changes.

Chapter 10, Columnstore Indexes, revises columnar storage and then explores the huge improvements relating to columnstore indexes in SQL Server 2016: updatable non-clustered columnstore indexes, columnstore indexes on in-memory tables, and many other new features for operational analytics.

Chapter 11, Introducing SQL Server In-Memory OLTP, describes a feature introduced in SQL Server 2014 that is still underused: the In-Memory database engine. This provides significant performance gains for OLTP workloads.

Chapter 12, In-Memory OLTP Improvements in SQL Server 2017, describes all the improvements to the In-Memory OLTP technology in SQL Server 2017. These improvements extend the number of potential use cases and allow implementation with less development effort and risk.

Chapter 13, Supporting R in SQL Server, introduces R Services and the R language. The chapter explains how SQL Server R Services combine the power and flexibility of the open source R language with enterprise-level tools for data storage and management, workflow development, and reporting and visualization.

Chapter 14, Data Exploration and Predictive Modeling with R, in SQL Server, shows how you can use R for advanced data exploration and manipulation, statistical analysis, and predictive modeling. All this is way beyond what is possible when using the T-SQL language.

Chapter 15, Introducing Python, teaches the Python basics and how to use the language inside SQL Server.

Chapter 16, Graph Databases, provides an overview of graph database architecture and how to create database objects in SQL Server 2017.

Chapter 17, Containers and SQL on Linux, introduces the two technologies mentioned in the chapter title and provides an overview of how to get started using them both.

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