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

Temporal Tables

Databases that serve business applications often need to support temporal data. For example, suppose a contract with a supplier is valid for a limited time only. It could be valid from a specific point in time onward, or it could be valid for a specific time interval—from a starting time point to an ending time point. In addition, often you'll need to audit all changes in one or more tables. You might also need to be able to show the state at a specific point in time, or all changes made to a table in a specific period of time. From a data integrity perspective, you might need to implement many additional temporal-specific constraints.

This chapter introduces temporal problems, deals with manual solutions, and shows you out-of-the-box features in SQL Server 2016 and 2017, including the following:

  • Defining temporal data
  • Using temporal data in SQL Server...