I use the solution in my company for real-time analytics on IoT data.
Azure Stream Analytics was not meeting our company's expectations because it was tedious to change the job, write queries, or if I needed to change something, I needed to stop the entire stream processing to change the job so that the changes could take effect. The aforementioned reasons were concerning, but I think that many of the issues related to the product have been resolved with the help of Microsoft Fabric.
The only challenge was that the streaming analytics area in Azure Stream Analytics could not meet our company's expectations, making it a component where improvements are required.
I have been using Azure Stream Analytics for two and a half years. My company has a partnership with Microsoft.
Azure Stream Analytics is a scalable solution.
My company deals with small, medium, and enterprise-sized customers for the product.
The solution's technical support is good. As soon as Microsoft's product team gets involved with the product, the support that our company receives from Microsoft is good. I rate the technical support a ten out of ten.
I also use Microsoft Fabric.
Azure Stream Analytics is easy to deploy. Other than the streaming analytics part, the rest of the areas in the product were fine. Templates were available in the product for the deployment process. The product's deployment process and connectivity were smooth. Scaling options in the product are good.
The solution can be deployed in a couple of minutes.
The product's price is at par with the other solutions provided by the other cloud service providers in the market.
Against Azure Stream Analytics, I had considered products like Amazon Kinesis and Google Cloud Dataflow.
Azure Stream Analytics for anomaly detection was something that was not meeting our company's expectations, but the new tool within Microsoft Fabric for real-time analytics is really good for even Azure Stream Analytics as it allows me to get alerts and use data activators, so I can take instantaneous actions. Regarding anomaly detection, it is much easier and faster with the availability of an SQL database, which is a real-time database. Within Microsoft Fabric, there is a component called real-time analytics, which consists of multiple tools like Eventstream, KQL database, and data activator.
Speaking about Microsoft Fabirc's features that were valuable for processing large volumes of data in real-time, I would say that our company is able to process a terabyte of data daily in real-time. The scaling part of the is outstanding, and the connectivity between the components is smooth. For the overall experience provided by Microsoft Fabric, I rate the tool a ten on ten if I specifically consider real-time analytics. Within Azure Stream Analytics, real-time analytics was not good, but in Microsoft Fabric, it is.
The product's integration capabilities have always been good since I could integrate multiple sources and ingest data.
Though my company has a maintenance team, the product does not need to be maintained as such. It is when we receive alerts in our company that we check the product. Dedicated maintenance or support is not required for the product.
Learning to use the product is a straightforward and easy process. I find AWS to be a bit confusing compared to Azure Stream Analytics.
Compared to Azure Stream Analytics, Amazon Kinesis, and Google Cloud Dataflow, I find Microsoft Fabric to be the best.
I rate Microsoft Fabric a ten out of ten.
I rate Azure Stream Analytics as seven to seven and a half out of ten.