We performed a comparison between Cloudera DataFlow and Spring Cloud Data Flow based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Amazon, Confluent and others in Streaming Analytics."DataFlow's performance is okay."
"The initial setup was not so difficult"
"This solution is very scalable and robust."
"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."
"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 is very user-friendly."
"The most valuable feature is real-time streaming."
"It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning."
"Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages."
"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"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."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
Cloudera DataFlow is ranked 13th in Streaming Analytics with 3 reviews while Spring Cloud Data Flow is ranked 10th in Streaming Analytics with 5 reviews. Cloudera DataFlow is rated 6.6, while Spring Cloud Data Flow is rated 8.0. The top reviewer of Cloudera DataFlow writes "A scalable and robust platform for analyzing data". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Good logging mechanisms, a strong infrastructure and pretty scalable". Cloudera DataFlow is most compared with Databricks, Confluent, Amazon MSK, Hortonworks Data Platform and Informatica Data Engineering Streaming, whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and Mule Anypoint Platform.
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.