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Introducing Microsoft SQL Server 2019

You're reading from   Introducing Microsoft SQL Server 2019 Reliability, scalability, and security both on premises and in the cloud

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781838826215
Length 488 pages
Edition 1st Edition
Languages
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Authors (8):
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Allan Hirt Allan Hirt
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Allan Hirt
Dustin Ryan Dustin Ryan
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Dustin Ryan
Mitchell Pearson Mitchell Pearson
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Mitchell Pearson
Kellyn Gorman Kellyn Gorman
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Kellyn Gorman
Dave Noderer Dave Noderer
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Dave Noderer
Buck Woody Buck Woody
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Buck Woody
Arun Sirpal Arun Sirpal
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Arun Sirpal
James Rowland-Jones James Rowland-Jones
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James Rowland-Jones
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Toc

Table of Contents (15) Chapters Close

Preface 1. Optimizing for performance, scalability and real‑time insights 2. Enterprise Security FREE CHAPTER 3. High Availability and Disaster Recovery 4. Hybrid Features – SQL Server and Microsoft Azure 5. SQL Server 2019 on Linux 6. SQL Server 2019 in Containers and Kubernetes 7. Data Virtualization 8. Machine Learning Services Extensibility Framework 9. SQL Server 2019 Big Data Clusters 10. Enhancing the Developer Experience 11. Data Warehousing 12. Analysis Services 13. Power BI Report Server 14. Modernization to the Azure Cloud

Introducing data virtualization

Data virtualization is the name given to any approach that enables you to query across disparate systems from a single source without having to know where that data physically resides.

Queries can be executed against a wide variety of relational and non-relational datasets, some of which may have their own compute engines, while others may not. When a remote compute engine exists, data virtualization technology enables you to push down computation to that data source. Advanced data virtualization engines also provide additional transparent caching of data to reduce the impact on the source system. These capabilities achieve a number of important benefits, which are summarized here for you:

  • Consolidate query processing at the source, reducing spend on resources.
  • Manage a single, semantic, and logical view of your data, avoiding duplication.
  • Address data issues at the source, improving data quality.
  • Query disparate data in real...
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