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Azure Stream Analytics

Score8 out of 10

3 Reviews and Ratings

What is Azure Stream Analytics?

Microsoft offers Azure Stream Analytics for IoT and connected devices, supporting real-time analytics and reporting.

Categories & Use Cases

Top Performing Features

  • Low Latency

    How many milli-seconds or seconds it takes to ingest, analyze and respond to an incoming event or data-point

    Category average: 8.7

  • Real-Time Data Analysis

    Ability to analyze data in motion

    Category average: 8.6

  • Data Ingestion from Multiple Data Sources

    Ability to ingest data from many sources including Internet of Things (IoT) endpoint data, stock trading data etc, as well as static data

    Category average: 8.8

Areas for Improvement

  • Data Enrichment

    Ability to enrich the data stream with static reference data

    Category average: 7.8

  • Linear Scale-Out

    Easy to scale out or scale down by visually changing the resource allocation. This allows changes in load or traffic to be handled without interruptions

    Category average: 7.6

  • Integrated Development Tools

    Tools to allow developers to rapidly create streaming applications via a graphical user interface and selection of predefined functions and operators

    Category average: 7.4

Stream analytics for real time processing

Use Cases and Deployment Scope

Azure Stream Analytics is used to calculate the cycle time from the tags also it is responsible for data enrichment for further calculations.

Pros

  • Routing of data from multiple inputs to multiple output
  • You create your own user define function.
  • Intermediate query is working very effectively.

Cons

  • Code competency is not that much effective
  • Ml models can't be integrated with stream analytics

Return on Investment

  • Very nice roi while using it.
  • Multiple integration is the best functionality

Alternatives Considered

AWS IoT Analytics

Other Software Used

Azure Event Hubs, Microsoft Azure IoT Hub, Microsoft Azure IoT Edge