Book Image

Introducing Microsoft SQL Server 2019

By : Kellyn Gorman, Allan Hirt, Dave Noderer, Mitchell Pearson, James Rowland-Jones, Dustin Ryan, Arun Sirpal, Buck Woody
Book Image

Introducing Microsoft SQL Server 2019

By: Kellyn Gorman, Allan Hirt, Dave Noderer, Mitchell Pearson, James Rowland-Jones, Dustin Ryan, Arun Sirpal, Buck Woody

Overview of this book

Microsoft SQL Server comes equipped with industry-leading features and the best online transaction processing capabilities. If you are looking to work with data processing and management, getting up to speed with Microsoft Server 2019 is key. Introducing SQL Server 2019 takes you through the latest features in SQL Server 2019 and their importance. You will learn to unlock faster querying speeds and understand how to leverage the new and improved security features to build robust data management solutions. Further chapters will assist you with integrating, managing, and analyzing all data, including relational, NoSQL, and unstructured big data using SQL Server 2019. Dedicated sections in the book will also demonstrate how you can use SQL Server 2019 to leverage data processing platforms, such as Apache Hadoop and Spark, and containerization technologies like Docker and Kubernetes to control your data and efficiently monitor it. By the end of this book, you'll be well versed with all the features of Microsoft SQL Server 2019 and understand how to use them confidently to build robust data management solutions.
Table of Contents (15 chapters)

SQL Graph Database

SQL Graph Database has powerful features for analyzing complex data. In a graph database, relationships are a built-in feature that can be easily and dynamically changed.

Compare this to a relational database, where relationships are created at design time. While relationships can be modified, it is not efficient to do this dynamically. When using a relational database, there is a performance penalty for both reads and writes that gets worse as the relationships become more complex.

With traditional relational databases, relationships can be made between entities (tables), but they are somewhat fixed, cumbersome, and difficult to maintain and change.

A graph database organizes data into nodes and edges. A node might represent a person, product, sale, address, or any other information that you would store in a relational table.

Relationships are stored in edges, which can be dynamically updated and express relationships as one-way or two-way. There...