At present, we’re asserting that Microsoft has been named a Chief in The Forrester Wave™: Streaming Analytics, Q2 2021. We imagine this report really displays the market momentum of Azure Stream Analytics, glad prospects, a rising companion ecosystem, and the general power of our Azure cloud platform. Check out the Forrester Wave™: Streaming Analytics, Q2 2021 report.
The Forrester Wave™: Streaming Analytics, Q2 2021 report evaluated streaming analytics choices from 14 completely different resolution suppliers, and we’re honored to share that Forrester has acknowledged Microsoft as a Chief on this class. Azure Stream Analytics acquired the best rating in twelve completely different classes together with efficiency, means to execute, resolution roadmap, buyer adoption, and extra.
The report states, “Microsoft makes world-class streaming analytics straightforward to make use of on cloud and edge. Azure Streaming Analytics lets builders use SQL to outline a wealthy set of streaming analytics queries. Behind the scenes of those streaming analytics queries, the Azure Streaming Analytics service optimizes the underlying sources to maximise throughput and latency. Notable and distinctive for a cloud service supplier is that streaming analytics queries can run on each the cloud and the sting utilizing Azure IoT Edge. Azure Streaming Analytics’ candy spot is for enterprises that want a cloud-scale streaming analytics functionality and or a mix of cloud-scale streaming analytics and edge streaming analytics.”
Our key differentiators for streaming analytics
Finest at school integration
Azure Stream Analytics is seamlessly built-in with the remainder of the Azure Ecosystem: in few clicks, you’ll be able to construct highly effective pipelines processing knowledge from IoT Hub, or Occasion Hub (together with Occasion Hubs from Apache Kafka functions) and generate real-time perception for dynamic dashboarding, real-time functions, massive scale analytics, or long-term storage. Examples of outputs embrace Azure SQL Databases, Azure Cosmos DB, Azure Synapse Analytics, Energy BI, and extra. Moreover, by leveraging Logic Apps wealthy set of connectors, customers can even join their streaming pipelines to a whole lot of third-party apps.
Ease of use
One of many benefits of Azure Stream Analytics is its easy SQL question language with highly effective temporal constraints to investigate knowledge in movement. Familiarity with SQL language is sufficient to creator highly effective queries.
As a part of our dedication to simplify the end-to-end analytics journey, we’re working to additional combine our distinctive low-latency streaming know-how into Azure Synapse Analytics.
Moreover, we at the moment are providing a no-code expertise for streaming analytics with Energy BI Streaming dataflows, enabling organizations to simply create end-to-end pipelines and productize them for real-time dashboards.
Azure Stream Analytics is designed for mission-critical eventualities. With the assure of no knowledge loss, exactly-once processing, and repeatability—it’s used for among the most necessary streaming pipelines inside Microsoft and is used to run vital workloads for 1000’s of shoppers.
The design of Azure Stream Analytics allows organizations to immediately scale out the processing energy from one to a whole lot of streaming items for any job to get extra processing energy when wanted.
With 99.9 % availability assured on the minute degree, Azure Stream Analytics affords industry-leading service-level settlement (SLA) traits.
As a part of our dedication to safety, Azure Stream Analytics supplies enhanced safety in your knowledge, supporting VNET, encryption of personal belongings with Buyer Managed Keys. Moreover, with connections to different sources with Managed Identities, we offer excessive safety whereas eradicating the necessity to outline and rotate connection strings, simplifying platform upkeep.
With its highly effective SQL language, Azure Stream Analytics supplies a big selection of analytic capabilities similar to native help for geospatial features, integration with machine studying for real-time scoring, built-in machine studying fashions for Anomaly Detection, sample matching, and extra to assist builders rapidly construct low-latency streaming analytics.
As latency and bandwidth are sometimes key necessities of streaming analytics, we permit organizations to course of knowledge as shut as attainable to the place it’s generated. To help this situation, our product is accessible within the cloud worldwide for cloud-scale analytics (at present in 30 plus Azure areas, extra to return), and can even run on IoT Edge or Azure Stack.