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Azure Stream Analytics

Serverless real-time analytics, from the cloud to the edge

Deliver powerful insights from your streaming data with ease, in real time

Discover Azure Stream Analytics, the easy-to-use, real-time analytics service that is designed for mission-critical workloads. Build an end-to-end serverless streaming pipeline with just a few clicks. Go from zero to production in minutes using SQL – easily extensible with customised code and built-in machine learning capabilities for more advanced scenarios. Run your most demanding workloads with the confidence of a financially backed SLA.

End-to-end analytics pipeline that is production-ready in minutes with familiar SQL syntax and extensible with JavaScript and C# customised code

Rapid scalability with elastic capacity to build robust streaming data pipelines and analyse millions of events at subsecond latencies

Hybrid architectures for stream processing with the ability to run the same queries in the cloud and on the edge

Enterprise-grade reliability with built-in recovery and built-in machine learning capabilities for advanced scenarios

Build streaming pipelines in minutes

Run complex analytics with no need to learn new processing frameworks or provision virtual machines (VMs) or clusters. Use familiar SQL language that is extensible with JavaScript and C# customised code for more advanced use cases. Easily enable scenarios like low-latency dashboarding, streaming ETL, and real-time alerting with one-click integration across sources and sinks.

Get started with real-time analytics on Azure

Run mission-critical workloads with subsecond latencies

Get guaranteed, “exactly once” event processing with 99.9% availability and built-in recovery capabilities. Easily set up a continuous integration and continuous delivery (CI-CD) pipeline and achieve subsecond latencies on your most demanding workloads.

Learn how to deploy an Azure Stream Analytics job with CI-CD

Deploy in the cloud and on the edge

Bring real-time insights and analytics capabilities closer to where your data originates. Enable new scenarios with true hybrid architectures for stream processing and run the same query in the cloud or on the edge.

Learn more about real-time analytics on the edge

Power real-time analytics with artificial intelligence

Take advantage of built-in machine learning (ML) models to shorten time to insights. Use ML-based capabilities to perform anomaly detection directly in your streaming jobs with Azure Stream Analytics.

Learn more about built-in machine learning for streaming jobs

Build a secure streaming solution with enhanced security and compliance from Azure

  • In-memory processing, with encrypted checkpointing
  • Encryption of all incoming and outgoing communications
  • Meets international and industry-specific security and compliance standards, including HIPAA, HITRUST, CSA STAR, and ISO/SOC requirements
  • Get guaranteed 99.9% SLA with Stream Analytics Dedicated. Our single tenant offering provides all the features of Standard ASA, in addition to VNET support using private endpoints.

Scale up rapidly and pay only for what you use

  • Pay only for the virtual machines and the associated storage and networking resources consumed
  • Take advantage of no-charge cluster management

Training resources for developers


Explore tutorials, samples, and other documentation to learn how to use Azure Stream Analytics.

Learning modules

Expand your knowledge and earn certifications with hands-on online courses from Microsoft Learn.

Browse training at Microsoft Learn

Start delivering solutions in days, instead of weeks or months

Create your Azure free account and get started with 12 months of free services.

Start quickly with a few clicks and create a Stream Analytics job using the Azure portal.

Community and Azure support

Ask questions and get support from Microsoft engineers and Azure community experts on MSDN and Stack Overflow, or chat with an Azure support specialist.

Popular templates and labs

Discover self-paced labs and popular quickstart templates for common configurations made by Microsoft and the community.

See what companies are achieving with Azure Stream Analytics

Global energy company optimises operations and drives real-time insights

ExxonMobil overcomes the challenges of monitoring and optimising a vast number of widely dispersed field assets with Azure analytics solutions.


World-famous brewers capture and process real-time data on a global scale

Find out how Anheuser Busch InBev uses Azure data services including Azure Stream Analytics to optimise inventory, reduce out-of-stock scenarios, and better forecast future retailer consumption trends.

AB InBev

International airport improves transportation traffic with real-time dashboards and Power BI

Heathrow Airport uses Azure to pull data out of back-end business systems and push it to Power BI, giving employees insights into airport passenger traffic in real time.


Kohler brings kitchens and baths into the smart home revolution with Azure IoT

Discover how Kohler is able to cut its development cycle in half and significantly lower startup investment with Azure data services and infrastructure.


Gaming studio innovates in real time to deliver fun new features and engage their players

Fluffy Fairy Games uses Azure to process billions of events, launch new features quickly, analyse player feedback and innovate to meet their users’ preferences.

Kolibri Games

Energy provider enhances storm recovery and customer service with real-time asset tracking

Learn how Southern Company uses Stream Analytics and IoT Hub to transform sensor data into actionable insights, relying on the elasticity and reliability of Azure for critical workloads.

Southern Company

Stream Analytics updates, blogs, and announcements

Frequently asked questions about Azure Stream Analytics

  • Azure Stream Analytics is available in 24 regions worldwide.
  • We guarantee at least 99.9 percent availability for the Stream Analytics API.
  • A standard streaming unit is a blend of compute and memory.
  • Streaming units are billed hourly, based on the maximum number of units selected during the hour.

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