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."The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"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 most valuable features are the IoT hub and the Blob storage."
"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time."
"It's scalable as a cloud product."
"It provides the capability to streamline multiple output components."
"The solution's most valuable feature is its ability to create a query using SQ."
"It's a product that can scale."
"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 support team is good and it's easy to use."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"The service is relatively cheap compared to other batch-processing engines."
"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."
"It is a scalable solution."
"The solution allows us to program in any language we desire."
"If something goes wrong, it's very hard to investigate what caused it and why."
"The initial setup is complex."
"I would like to have a contact individual at Microsoft."
"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 solution's interface could be simpler to understand for non-technical people."
"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."
"The collection and analysis of historical data could be better."
"The UI should be a little bit better from a usability perspective."
"Google Cloud Dataflow should include a little cost optimization."
"The deployment time could also be reduced."
"The technical support has slight room for improvement."
"The solution's setup process could be more accessible."
"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."
"The authentication part of the product is an area of concern where improvements are required."
"They should do a market survey and then make improvements."
"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."
Azure Stream Analytics is ranked 3rd 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.