Събитие
31.03, 23 ч. - 2.04, 23 ч.
Най-голямото събитие за обучение на Fabric, Power BI и SQL. 31 март – 2 април. Използвайте код FABINSIDER, за да спестите $400.
Регистрирайте се днесТози браузър вече не се поддържа.
Надстройте до Microsoft Edge, за да се възползвате от най-новите функции, актуализации на защитата и техническа поддръжка.
There are several services available for real-time analytics and streaming processing on Azure. This article provides the information you need to decide which technology is the best fit for your application.
Azure Stream Analytics is the recommended service for stream analytics on Azure. You can use it for a wide range of scenarios that include but aren't limited to:
Adding an Azure Stream Analytics job to your application is the fastest way to get streaming analytics up and running in Azure, using the SQL language you already know. Azure Stream Analytics is a job service, so you don't have to spend time managing clusters, and you don't have to worry about downtime with a 99.9% Service Level Agreement (SLA) at the job level. Billing is also done at the job level making startup costs low (one Streaming Unit), but scalable (up to 396 Streaming Units). It's much more cost effective to run a few Stream Analytics jobs than it's to run and maintain a cluster.
Azure Stream Analytics has a rich out-of-the-box experience. You can immediately take advantage of the following features without any extra setup:
Azure Stream Analytics supports user-defined functions (UDF) or user-defined aggregates (UDA) in JavaScript for cloud jobs and C# for IoT Edge jobs. C# user-defined deserializers are also supported. If you want to implement a deserializer, a UDF, or a UDA in other languages, such as Java or Python, you can use Spark Structured Streaming. You can also run the Event Hubs EventProcessorHost on your own virtual machines to do arbitrary streaming processing.
Azure Stream Analytics is Microsoft's proprietary technology and is only available on Azure. If you need your solution to be portable across Clouds or on-premises, consider open-source technologies such as Spark Structured Streaming or Apache Flink.
Събитие
31.03, 23 ч. - 2.04, 23 ч.
Най-голямото събитие за обучение на Fabric, Power BI и SQL. 31 март – 2 април. Използвайте код FABINSIDER, за да спестите $400.
Регистрирайте се днесОбучение
Модул
Explore fundamentals of real-time analytics - Training
Learn about the basics of stream processing, and the services in Microsoft Azure that you can use to implement real-time analytics solutions.
Сертифициране
Microsoft Certified: Azure Data Engineer Associate - Certifications
Demonstrate understanding of common data engineering tasks to implement and manage data engineering workloads on Microsoft Azure, using a number of Azure services.