"Provides deep integration with other Azure resources."
"The most valuable features are the IoT hub and the Blob storage."
"I like the IoT part. We have mostly used Azure Stream Analytics services for it"
"It's a product that can scale."
"I like the way the UI looks, and the real-time analytics service is aligned to this. That can be helpful if I have to use this on a production service."
"The solution has a lot of functionality that can be pushed out to companies."
"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time."
"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."
"The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."
"The UI should be a little bit better from a usability perspective."
"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."
"The collection and analysis of historical data could be better."
"If something goes wrong, it's very hard to investigate what caused it and why."
"Early in the process, we had some issues with stability."
"There may be some issues when connecting with Microsoft Power BI because we are providing the input and output commands, and there's a chance of it being delayed while connecting."
"It is not complex, but it requires some development skills. When the data is sent from Azure Stream Analytics to Power BI, I don't have the access to modify the data. I can't customize or edit the data or do some queries. All queries need to be done in the Azure Stream Analytics."
"Azure Stream Analytics could improve by having clearer metrics as to the scale, more metrics around the data set size that is flowing through it, and performance tuning recommendations."
"Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job."
Earn 20 points
Azure Stream Analytics is ranked 5th in Streaming Analytics with 9 reviews while Google Cloud Dataflow is ranked 11th in Streaming Analytics with 1 review. Azure Stream Analytics is rated 8.0, while Google Cloud Dataflow is rated 8.0. The top reviewer of Azure Stream Analytics writes "A serverless scalable event processing engine with a valuable IoT feature". On the other hand, the top reviewer of Google Cloud Dataflow writes "Easy to use for programmers, user-friendly, and scalable". Azure Stream Analytics is most compared with Databricks, Amazon Kinesis, Apache Spark, Apache Flink and Confluent, whereas Google Cloud Dataflow is most compared with Apache NiFi, Apache Flink, Amazon Kinesis, Databricks and IBM Streams.
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