We performed a comparison between Azure Stream Analytics and Google Cloud Dataflow based on real PeerSpot user reviews.
Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We find the query editor feature of this solution extremely valuable for our business."
"We use Azure Stream Analytics for simulation and internal activities."
"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."
"I appreciate this solution because it leverages open-source technologies. It allows us to utilize the latest streaming solutions and it's easy to develop."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"Provides deep integration with other Azure resources."
"The solution's most valuable feature is its ability to create a query using SQ."
"The most valuable features are the IoT hub and the Blob storage."
"I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service."
"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 most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The solution allows us to program in any language we desire."
"The service is relatively cheap compared to other batch-processing engines."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"It is a scalable solution."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."
"The solution offers a free trial, however, it is too short."
"The collection and analysis of historical data could be better."
"Early in the process, we had some issues with stability."
"The solution could be improved by providing better graphics and including support for UI and UX testing."
"I would like to have a contact individual at Microsoft."
"The solution doesn't handle large data packets very efficiently, which could be improved upon."
"We would like to have centralized platform altogether since we have different kind of options for data ingestion. Sometimes it gets difficult to manage different platforms."
"The technical support has slight room for improvement."
"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."
"The solution's setup process could be more accessible."
"Google Cloud Dataflow should include a little cost optimization."
"I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool."
"When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs."
"They should do a market survey and then make improvements."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
Azure Stream Analytics is ranked 4th in Streaming Analytics with 22 reviews while Google Cloud Dataflow is ranked 7th in Streaming Analytics with 10 reviews. Azure Stream Analytics is rated 8.2, while Google Cloud Dataflow is rated 7.8. The top reviewer of Azure Stream Analytics writes "Easy to set up and user-friendly, but could be priced better". 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 Amazon Kinesis, Databricks, Amazon MSK, Apache Flink and Apache NiFi, whereas Google Cloud Dataflow is most compared with Databricks, Apache NiFi, Amazon MSK, Amazon Kinesis and Apache Spark. See our Azure Stream Analytics vs. Google Cloud Dataflow report.
See our list of best Streaming Analytics vendors.
We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.