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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
Author Profile Icon James Rowland-Jones
James Rowland-Jones
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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

Working with streaming data in Azure Stream Analytics

Azure Stream Analytics is an event-processing engine that allows you to analyze large volumes on streaming data in flight. Patterns and relationships can be identified in information extracted from a variety of input sources including devices, sensors, websites, social media feeds, and applications. The insights discovered can be used to trigger other actions as part of a workflow including creating alerts, feeding information to a reporting tool, or storing transformed data for later use.

Stream Analytics is ideal in scenarios related to real-time data warehousing. When used with event processing services such as Azure Event Hubs or Azure IoT Hub, Stream Analytics can be used to perform data cleansing, data reduction, and data store and forward needs. Stream Analytics can load data directly to Azure SQL Data Warehouse using the SQL output adapter, but throughput can be improved some increased latency by using PolyBase to read...

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