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Microsoft Azure Stream Analytics is a serverless scalable complex event processing engine by Microsoft 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. [1]
Azure Stream Analytics; Drools Fusion; Esper Complex event processing for Java and C# (GPLv2). Feedzai - Pulse; Microsoft StreamInsight Microsoft CEP Engine implementation [18] openPDC — A set of applications for processing streaming time-series data in real-time.
Azure Stream Analytics is a Serverless scalable event-processing engine that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, websites, social media, and other applications.
Azure Data Lake service was released on November 16, 2016. It is based on COSMOS, [2] which is used to store and process data for applications such as Azure, AdCenter, Bing, MSN, Skype and Windows Live.
Stream-processing technologies typically used in this layer include Apache Kafka, Amazon Kinesis, Apache Storm, SQLstream, Apache Samza, Apache Spark, Azure Stream Analytics, Apache Flink. Output is typically stored on fast NoSQL databases., [6] [7] or as a commit log. [8]
The unit that has most benefited from this partnership has been Azure, which is the No. 2 leading cloud computing company with a 20% market share. ... of its data and analytics services, Azure ...
By way of illustration, the following code fragments demonstrate detection of patterns within event streams. The first is an example of processing a data stream using a continuous SQL query (a query that executes forever processing arriving data based on timestamps and window duration).
Azure Data Explorer is a fully-managed [1] big data analytics cloud platform [2] [3] and data-exploration service, [4] developed by Microsoft, [5] [6] that ingests structured, semi-structured (like JSON) and unstructured data (like free-text).