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 use Azure Stream Analytics for simulation and internal activities."
"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."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"The life cycle, report management and crash management features are great."
"I like the IoT part. We have mostly used Azure Stream Analytics services for it"
"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 solution's most valuable feature is its ability to create a query using SQ."
"Technical support is pretty helpful."
"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 best feature of Google Cloud Dataflow is its practical connectedness."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"It is a scalable solution."
"The support team is good and it's easy to use."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"The solution allows us to program in any language we desire."
"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 solution’s customer support could be improved."
"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."
"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."
"Easier scalability and more detailed job monitoring features would be helpful."
"The UI should be a little bit better from a usability perspective."
"If something goes wrong, it's very hard to investigate what caused it and why."
"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 authentication part of the product is an area of concern where improvements are required."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"Google Cloud Dataflow should include a little cost optimization."
"They should do a market survey and then make improvements."
"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."
"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."
"The deployment time could also be reduced."
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 AWS Lambda, 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.
