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SQL Server Advanced Data Types

JSON, XML, and Beyond

  • Peter A. Carter

Table of contents

  1. Front Matter
    Pages i-xv
  2. Peter A. Carter
    Pages 1-28
  3. Peter A. Carter
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  14. Back Matter
    Pages 385-392

About this book

Introduction

Deliver advanced functionality faster and cheaper by exploiting SQL Server's ever-growing amount of built-in support for modern data formats. Learn about the growing support within SQL Server for operations and data transformations that have previously required third-party software and all the associated licensing and development costs. Benefit through a better understanding of what can be done inside the database engine with no additional costs or development time invested in outside software.

Widely used types such as JSON and XML are well-supported by the database engine. The same is true of hierarchical data and even temporal data. Knowledge of these advanced types is crucial to unleashing the full power that's available from your organization's SQL Server database investment. 

SQL Server Advanced Data Types explores each of the complex data types supplied within SQL Server. Common usage scenarios for each complex data type are discussed, followed by a detailed discussion on how to work with each data type. Each chapter demystifies the complex data and you learn how to use the data types most efficiently.

The book offers a practical guide to working with complex data, using real-world examples to demonstrate how each data type can be leveraged. Performance considerations are also discussed, including the implementation of special indexes such as XML indexes and spatial indexes.

What You'll Learn:
  • Understand the implementation of basic data types and why using the correct type is so important
  • Work with XML data through the XML data type
  • Construct XML data from relational result sets
  • Store and manipulate JSON data using the JSON data type
  • Model and analyze spatial data for geographic information systems
  • Define hierarchies and query them efficiently through the HierarchyID type

Keywords

XML JSON CLR Hierarchical data Spatial data HierarchyID Data storage and optimization Row compression Page compression XSD Schemas XQuery XML Indexes User Defined Types Geometry Data Type

Authors and affiliations

  • Peter A. Carter
    • 1
  1. 1.LondonUnited Kingdom

Bibliographic information