We performed a comparison between Amazon MSK and Spring Cloud Data Flow based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics."It offers good stability."
"The most valuable feature of Amazon MSK is the integration."
"MSK has a private network that's an out-of-box feature."
"It is a stable product."
"Overall, it is very cost-effective based on the workflow."
"Amazon MSK has significantly improved our organization by building seamless integration between systems."
"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."
"The product is very user-friendly."
"The most valuable feature is real-time streaming."
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"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 should be more flexible, integration-wise."
"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."
"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."
"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
Amazon MSK is ranked 6th in Streaming Analytics with 6 reviews while Spring Cloud Data Flow is ranked 9th in Streaming Analytics with 5 reviews. Amazon MSK is rated 7.2, while Spring Cloud Data Flow is rated 8.0. The top reviewer of Amazon MSK writes "Efficient real-time transaction tracking but time-consuming installation". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". Amazon MSK is most compared with Confluent, Amazon Kinesis, Azure Stream Analytics, Google Cloud Dataflow and PubSub+ Event Broker, whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and TIBCO BusinessWorks.
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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.
