We performed a comparison between Amazon MSK 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."MSK has a private network that's an out-of-box feature."
"Amazon MSK has significantly improved our organization by building seamless integration between systems."
"It is a stable product."
"Overall, it is very cost-effective based on the workflow."
"The most valuable feature of Amazon MSK is the integration."
"It offers good stability."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"It is a scalable solution."
"The solution allows us to program in any language we desire."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"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 service is relatively cheap compared to other batch-processing engines."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."
"It should be more flexible, integration-wise."
"The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET."
"The configuration seems a little complex and the documentation on the product is not available."
"It does not autoscale. Because if you do keep it manually when you add a note to the cluster and then you register it, then it is scalable, but the fact that you have to go and do it, I think, makes it, again, a bit of some operational overhead when managing the cluster."
"It would be really helpful if Amazon MSK could provide a single installation that covers all the servers."
"Google Cloud Dataflow should include a little cost optimization."
"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."
"They should do a market survey and then make improvements."
"The deployment time could also be reduced."
"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 solution's setup process could be more accessible."
"The technical support has slight room for improvement."
"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."
Amazon MSK is ranked 6th in Streaming Analytics with 6 reviews while Google Cloud Dataflow is ranked 7th in Streaming Analytics with 10 reviews. Amazon MSK is rated 7.2, while Google Cloud Dataflow is rated 7.8. The top reviewer of Amazon MSK writes "Efficient real-time transaction tracking but time-consuming installation". On the other hand, the top reviewer of Google Cloud Dataflow writes "Easy to use for programmers, user-friendly, and scalable". Amazon MSK is most compared with Confluent, Amazon Kinesis, Azure Stream Analytics, Aiven for Apache Kafka and Apache Pulsar, whereas Google Cloud Dataflow is most compared with Databricks, Apache NiFi, Amazon Kinesis, Spring Cloud Data Flow and Apache Flink. See our Amazon MSK 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.
