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.
相关问题
- running headless chrome in an microsoft azure web
- Docker task in Azure devops won't accept "$(pw
- Register MicroServices in Azure Active Directory (
- Removing VHD's from Azure Resource Manager aft
- Cannot use the Knowledge academic API
相关文章
- SQL Azure Reset autoincrement
- How to cast Azure DocumentDB Document class to my
- Can't get azure web role to run locally using
- Azure WebApp - Unable to auto-detect the runtime s
- How to change region for Azure WebSite
- Azure webjob vs cloud service
- Azure data transfer Identity Column Seed Jumped by
- Download Azure web app?
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.
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:
Stream Analytisc