Microsoft Adds Streaming Analytics to Azure
Microsoft Adds Streaming Analytics to Azure : Microsoft added three services Streaming Analytics, Data Production and Workflow Services to Azure. The Azure Stream Analytics, Azure Data Factory and Azure Event Hubs services capabilities help customers to process data from devices and sensors within the Internet of Things, and manage and orchestrate data across diverse sources.
Azure is an Internet scale computing and services platform hosted in data centers managed or supported by Microsoft. It includes many separate features with corresponding developer services which can be used individually or together. It is Microsoft’s cloud platform and a growing collection of integrated services to compute, storage, data, networking, and app.
The Azure Stream Analytics and Azure Data Factory are available in preview and Azure Event Hubs is now generally available.
Stream Analytics is a cost-effective event processing engine that helps uncover real-time insights from devices, sensors, infrastructure, applications and data quickly and easily. Azure Data Factory enables information production by orchestrating and managing diverse data and Azure Event Hubs is a scalable service for collecting data from millions of “things” in seconds.
Azure Stream Analytics is a fully managed service providing low latency, highly available, scalable complex event processing over streaming data in the cloud. Azure Stream Analytics is a fully managed real-time stream computation service hosted in Microsoft Azure, which provides highly resilient, low latency, and scalable complex event processing of streaming data. Azure Stream Analytics enables developers to easily combine streams of data with historic records or reference data to derive business insights easily and quickly.
With a few clicks in the Azure Portal, customers can author a streaming job using a SQL-like language to specify transformations and monitor the scale/speed of their overall streaming pipeline. The service can easily scale from a few kilobytes to a gigabyte or more of events processed per second. Most other streaming solutions available today require customers to write complex custom code, but with Azure Stream Analytics customers can write simple, declarative, familiar SQL.
Azure Stream Analytics provides a range of operators from simple filters to complex correlations. Defining time based windowed operations such as windowed aggregates, or correlating multiple streams to detect patterns such as sequences, or even comparing current conditions to historical values and models, can be done in a matter of minutes using the simple set of SQL-like Stream Analytics Query Language operators.
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