Book Image

Mastering SQL Server 2017

By : Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah
Book Image

Mastering SQL Server 2017

By: Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah

Overview of this book

Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation. You’ll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you’ll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks. By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence. This Learning Path includes content from the following Packt books: SQL Server 2017 Developer's Guide by Miloš Radivojevi?, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al
Table of Contents (20 chapters)
Title Page
Free Chapter
1
Introduction to SQL Server 2017

Introduction to SQL Server 2017

SQL Server is the main relational database management system product from Microsoft. It has been around in one form or another since the late 80s (developed in partnership with Sybase), but as a standalone Microsoft product, it's been here since the early 90s. In the last 20 years, SQL Server has changed and evolved, gaining newer features and functionality along the way.

The SQL Server we know today is based on what was arguably the most significant (r)evolutionary step in its history: the release of SQL Server 2005. The changes that were introduced allowed the versions that followed the 2005 release to take advantage of newer hardware and software improvements, such as: 64-bit memory architecture, better multi-CPU and multi-core support, better alignment with the .NET framework, and many more modernizations in general system architecture.

The incremental changes introduced in each subsequent version of SQL Server have continued to improve upon this solid new foundation. Fortunately, Microsoft has changed the release cycle for multiple products, including SQL Server, resulting in shorter time frames between releases. This has, in part, been due to Microsoft's focus on their much reported Mobile first, Cloud first strategy. This strategy, together with the development of the cloud version of SQL Server Azure SQL Database, has forced Microsoft into a drastically shorter release cycle. The advantage of this strategy is that we are no longer required to wait 3 to 5 years for a new release (and new features). There have been releases every 2 years since SQL Server 2012 was introduced, with multiple releases of Azure SQL Database in between the real versions.

While we can be pleased that we no longer need to wait for new releases, we are also at a distinct disadvantage. The rapid release of new versions and features leaves us developers with ever-decreasing periods of time to get to grips with the shiny new features. Prior versions had multiple years between releases, allowing us to build up a deeper knowledge and understanding of the available features, before having to consume new information.

Following on from the release of SQL Server 2016 was the release of SQL Server 2017, barely a year after 2016 was released. Many features were merely more polished/updated versions of the 2016 release, while there were some notable additions in the 2017 release.

In this chapter (and book), we will introduce what is new inside SQL Server 2017. Due to the short release cycle, we will outline features that are brand new in this release of the product and look at features that have been extended or improved upon since SQL Server 2016.

We will be outlining the new features in the following areas:

  • Security
  • Engine features
  • Programming
  • Business intelligence