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Introducing Microsoft SQL Server 2019

You're reading from  Introducing Microsoft SQL Server 2019

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

Table of Contents (15) Chapters close

Preface 1. Optimizing for performance, scalability and real‑time insights 2. Enterprise Security 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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