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What is Microsoft Azure Stream Analytics?

Microsoft Azure Stream Analytics (ASA) is a fully managed cloud service for real-time processing of streaming data.  ASA makes it easy to set up real-time analytic computations on data flowing in from devices, sensors, web sites, applications and infrastructure systems.  It supports a powerful high-level SQL-like language that dramatically simplifies the logic to visualize, alert, or act in near real-time.  ASA makes it simpler to build a wide range of Internet-of-Things (IoT) applications such as real-time remote device management, and to monitor and gain analytic insights from connected devices of all types including mobile phones and connected cars.

It was made generally available on April 16, 2015 (read).


ASA supports two different types of inputs, either stream data or reference data, and two different input data sources, either Azure Event Hubs or files from Azure Blob Storage.

The ingestor, or data source, for stream analytics is usually an Azure Event Hub.  Event Hubs is a highly scalable publish-subscribe data integrator capable of consuming large volumes of events per second, enabling Azure to process vast amounts of data from connected applications or devices.  It provides a unified collection point for a broad array of platforms and devices, and as such, abstracts the complexity of ingesting multiple different input streams directly into the streaming analytics engine.  ASA has an Event Hubs adapter built into the offering.

ASA supports five different types of outputs: Blob storage, Event Hub, Power BI, SQL Database or Table Storage.  ASA also enhances SQL by supporting groupings by time (see Windowing).  ASA provides a native connector for SQL Database for consuming events that are output from the stream.

One of the common presentation use cases for ASA is to analyze high volume streaming data in real-time and get the insight in a live dashboard (a dashboard that updates in real-time without user having to refresh the browser).  You can build a live dashboard using Power BI as an output for your ASA job (see Azure Stream Analytics & Power BI: Live dashboard for real-time analytics of streaming data).

It is real easy to build an ASA solution as it is all done thru the Azure web portal.  There is no need to create a VM and remote into it.  It is also possible to easily integrate with Azure ML.

There are also a couple of tutorials you can check out if you want to build a end-to-end solution.

Microsoft has two other stream processing platforms: StreamInsight and Azure HDInsight Storm.

More info:

Stream Analytics documentation

Reference Architecture: Real-time event processing with Microsoft Azure Stream Analytics

Video An Introduction to Azure Stream Analytics

Video Gaining Real-Time IoT Insights using Azure Stream Analytics, AzureML and PowerBI

Azure Stream Analytics Team Blog

Video Azure Stream Analytics Demo

Building an IoT solution with Azure Event Hubs and Stream Analytics – Part 3

How to Process Google Data in Real Time with Azure Stream Analytics

Microsoft Azure Stream Analytics

James Serra's Blog

James is a big data and data warehousing technology specialist at Microsoft. He is a thought leader in the use and application of Big Data technologies, including MPP solutions involving hybrid technologies of relational data, Hadoop, and private and public cloud. Previously he was an independent consultant working as a Data Warehouse/Business Intelligence architect and developer. He is a prior SQL Server MVP with over 30 years of IT experience. James is a popular blogger (JamesSerra.com) and speaker, having presented at dozens of PASS events including the PASS Business Analytics conference and the PASS Summit. He is the author of the book “Reporting with Microsoft SQL Server 2012”. He received a Bachelor of Science degree in Computer Engineering from the University of Nevada-Las Vegas.


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