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 most valuable features are the IoT hub and the Blob storage."
"Provides deep integration with other Azure resources."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"It's scalable as a cloud product."
"It's a product that can scale."
"We find the query editor feature of this solution extremely valuable for our business."
"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's most valuable feature is its ability to create a query using SQ."
"It is a scalable solution."
"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 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."
"The support team is good and it's easy to use."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"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."
"I would like to have a contact individual at Microsoft."
"If something goes wrong, it's very hard to investigate what caused it and why."
"The solution's interface could be simpler to understand for non-technical people."
"Easier scalability and more detailed job monitoring features would be helpful."
"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 collection and analysis of historical data could be better."
"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."
"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 authentication part of the product is an area of concern where improvements are required."
"The solution's setup process could be more accessible."
"The technical support has slight room for improvement."
"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."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"Google Cloud Dataflow should include a little cost optimization."
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.