Azure Storm vs Azure Stream Analytics

2019-06-17 06:43发布

问题:

Looking to do real time metric calculations on event streams, what is a good choice in Azure? Stream Analytics or Storm? I am comfortable with either SQL or Java, so wondering what are the other differences.

回答1:

It depends on your needs and requirements. I'll try to lay out the strengths and benefits of both. In terms of setup, Stream Analytics has Storm beat. Stream Analytics is great if you need to ask a lot of different questions often. Stream Analytics can also only handle CSV or JSON type data. Stream Analytics is also at the mercy of only sending outputs to Azure Blob, Azure Tables, Azure SQL, PowerBI; any other output will require Storm. Stream Analytics lacks the data transformation capabilities of Storm.

Storm:

  • Data Transformation
  • Can handle more dynamic data (if you're willing to program)
  • Requires programming

Stream Analytisc

  • Ease of Setup
  • JSON and CSV format only
  • Can change queries within 4 minutes
  • Only takes inputs from Event Hub, Blob Storage
  • Only outputs to Azure Blob, Azure Tables, Azure SQL, PowerBI


回答2:

If you are looking for versatility over flexibility. I'd go with Stream Analytics, if you require specific operations that are limited by Stream Analytics, it's worth looking into Spark, which gives you data persistence options. On the Stream Analytics outputs side, one interesting thing would be to output into an Event Hub and consume it from there giving you unlimited flexibility on how you want to consume the data.

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

Hope this helps.