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Microsoft Azure Stream Analytics is a serverless scalable
complex event processing Event processing is a method of tracking and analyzing (processing) streams of information (data) about things that happen (events), and deriving a conclusion from them. Complex event processing, or CEP, consists of a set of concepts and techniques ...
engine by
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that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, web sites, social media, and other applications. Users can set up alerts to detect anomalies, predict trends, trigger necessary workflows when certain conditions are observed, and make data available to other downstream applications and services for presentation, archiving, or further analysis.


Query Language

Users can author real-time analytics using a simple declarative SQL-like language with embedded support for temporal logic. Callouts to custom code with
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user defined functions extend the streaming logic written in SQL. Callouts to Azure Machine Learning helps with predictive scoring on streaming data.


Scalability

Azure Stream Analytics is a serverless job service on Azure that eliminates the need for infrastructure, servers, virtual machines, or managed clusters. Users only pay for the processing used for the running jobs.


IoT applications

Azure Stream Analytics integrates with Azure IoT Hub to enable real-time analytics on data from IoT devices and applications.


Real-time Dashboards

Users can build real-time dashboards with
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for a live command and control view. Real-time dashboards help transform live data into actionable and insightful visuals.


Data Input Sources

Stream Analytics supports three different types of input sources - Azure Event Hubs, Azure IoT Hubs, and Azure Blob Storage. Additionally, stream analytics supports Azure Blob storage as the input reference data to help augment fast moving event data streams with static data. Stream analytics supports a wide variety of output targets. Support for Power BI allows for real-time dashboarding. Event Hub, Service bus topics and queues help trigger downstream workflows. Support for Azure Table Storage, Azure SQL Databases,
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, Azure SQL, Document DB,
Azure Data Lake Azure Data Lake is a scalable data storage and analytics service. The service is hosted in Azure, Microsoft's public cloud. History Azure Data Lake service was released on November 16, 2016. It is based on COSMOS, which is used to store and pr ...
Store enable a variety of downstream analysis and archiving capabilities.


References


External links

* {{Microsoft Azure Services Platform, state=expanded Cloud computing Cloud computing providers Cloud infrastructure Cloud platforms Microsoft cloud services