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Azure Storm vs Azure Stream Analytics

Want to do real-time metric calculations in event streams, which is a good choice in Azure? Stream Analytics or Storm? I like either SQL or Java, so we wonder what the other differences are.

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2 answers

It depends on your needs and requirements. I will try to lay out the strengths and advantages of both. In terms of customization, Stream Analytics has a Storm beat. Stream Analytics is great if you need to ask a lot of different questions often. Stream Analytics can also only process data like CSV or JSON. Stream Analytics is also in the power of only sending out Azure Blob, Azure Tables, Azure SQL, PowerBI; any other way out will require a storm. Stream Analytics lacks the ability to transform Storm data.

Stormy:

  • Data conversion
  • Can handle more dynamic data (if you want to program)
  • Programming required

Stream analytisc

  • Easy installation
  • JSON and CSV format only
  • Can change requests within 4 minutes
  • Accepts only input from Event Hub, Blob Storage
  • Only outputs for Azure Blob, Azure Tables, Azure SQL, PowerBI
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If you are looking for versatility in flexibility. I would go with Stream Analytics, if you need specific operations that are limited by Stream Analytics, it's worth looking at Spark, which gives you options for saving data. On the output side of Stream Analytics, one interesting thing is to bring it to the event hub and destroy it from there, giving you unlimited flexibility regarding how you want to use the data.

Below are the output options for Stream Analytics and the link for Apache Spark on Azure

Hope this helps.

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Source: https://habr.com/ru/post/989988/

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