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Processing Big data in real-time is an operational necessity for many businesses. Azure Stream Analytics is Microsoft’s serverless real-time analytics offering for complex event processing.

We are excited and humbled to announce that Microsoft has been named a leader in The Forrester Wave™: Streaming Analytics, Q3 2019. Microsoft believes this report truly reflects the market momentum of Azure Stream Analytics, satisfied customers, a growing partner ecosystem and the overall strength of our Azure cloud platform. You can access the full report here.

Forrester Wave for Streaming Analytics published in Q3 2019 that positions Microsoft as a leader in the category.


The Forrester Wave™: Streaming Analytics, Q3 2019


Forrester Wave™: Streaming Analytics, Q3 2019 report evaluated streaming analytics offerings from 11 different solution providers and we are honored to share that that Forrester has recognized Microsoft as a Leader in this category. Azure Stream Analytics received the highest possible score in 12 different categories including Ability to execute, Administration, Deployment, Solution Roadmap, Customer adoption and many more.

The report states, “Microsoft Azure Stream Analytics has strengths in scalability, high availability, deployment, and applications. Azure Stream Analytics is an easy on-ramp for developers who already know SQL. Zero-code integration with over 15 other Azure services makes it easy to try and therefore adopt, making the product the real-time backbone for enterprises needing real-time streaming applications on the Azure cloud. Additionally, through integration with IoT Hub and Azure Functions, it offers seamless interoperability with thousands of devices and business applications.”

Key Differentiators for Azure Stream Analytics

Fully integrated with Azure ecosystem: Build powerful pipelines with few clicks

Whether you have millions of IoT devices streaming data to Azure IoT Hub or have apps sending critical telemetry events to Azure Event Hubs, it only takes a few clicks to connect multiple sources and sinks to create an end-to-end pipeline.

Developer productivity

One of the biggest advantages of Stream Analytics is the simple SQL-based query language with its powerful temporal constraints to analyze data in motion. Familiarity with SQL language is enough to author powerful queries. Additionally, Azure Stream Analytics supports language extensibility via C# and JavaScript user-defined functions (UDFs) or user-defined aggregates to perform complex calculations as part of a Stream Analytics query.

Analytics prowess

Stream Analytics contains a wide array of analytic capabilities such as native support for geospatial functions, built-in callouts to custom machine learning (ML) models for real-time scoring, built-in ML models for Anomaly Detection, Pattern matching, and more to help developers easily tackle complex scenarios while staying in a familiar context.

Intelligent edge

Azure Stream Analytics helps bring real-time insights and analytics capabilities closer to where your data originates. Customers can easily enable new scenarios with true hybrid architectures for stream processing and run the same query in the cloud or on the IoT edge.

Best-in-class financially backed SLA by the minute

We understand it is critical for businesses to prevent data loss and have business continuity. Stream Analytics guarantees event processing with a 99.9 percent availability service-level agreement (SLA) at the minute level, which is unparalleled in the industry.

Scale instantly

Stream Analytics is a fully managed serverless (PaaS) offering on Azure. There is no infrastructure to worry about, and no servers, virtual machines, or clusters to manage. We do all the heavy lifting for you in the background. You can instantly scale up or scale-out the processing power from one to hundreds of streaming units for any job.

Mission critical

Stream Analytics guarantees “exactly once” event processing and at least once delivery of events. It has built-in recovery capabilities in case the delivery of an event fails. So, you never have to worry about your events getting dropped.

Try it today

There is a strong and growing developer community that supports Stream Analytics. Learn how to get started and build a real-time fraud detection system.

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