We performed a comparison between Spring Cloud Data Flow and WhereScape RED based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."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 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."
"Quickly develops a data warehouse for our organization with documentation and can track back/forward features."
"I like the data vault implementations."
"It has a built-in automatic scheduling environment."
"The tool supports multiple target update methods."
"Data transformations and rollups are easy to accomplish."
"Naturally produces a way to easily debug your DW data solutions."
"Their support staff are very knowledgeable, courteous, and professional. I feel their support staff go above and beyond to assure their customers are satisfied."
"RED has provided us the ability to integrate, stage, and transform data from diverse sources into an enterprise-grade data warehouse which meets the needs of my organization, but it also enables us to easily and quickly make ETL or DW changes."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"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."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"The solution can be a little more user-friendly on enterprise-level where people use it."
"The scheduled jobs which are run by the WhereScape scheduler seem to be a strangely separate animal. Unlike all other WhereScape objects, jobs cannot be added to WhereScape projects. Also, unlike all other objects, jobs also cannot be deleted using a WhereScape deployment application."
"Technical support isn't the best."
"Project-based searching of data objects in the data warehouse browser needs to be improved."
"The ability to execute SSIS projects within WhereScape would be nice because we have a lot of packages that are too cumbersome to recreate."
"Jobs cannot be deleted via the deployment package. When deploying from dev to QA or production, a job has to be retired. The job has to be manually removed from the target environment."
"It could use a tool to diagnose what is missing from the environment for WhereScape to install successfully."
"They need a more robust support center. It has been a bit difficult to find solutions to problems that are out-of-the-box."
Earn 20 points
Spring Cloud Data Flow is ranked 29th in Data Integration with 5 reviews while WhereScape RED is ranked 48th in Data Integration. Spring Cloud Data Flow is rated 8.0, while WhereScape RED is rated 8.2. The top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". On the other hand, the top reviewer of WhereScape RED writes "Quick to set up, flexible, and stable". Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and TIBCO BusinessWorks, whereas WhereScape RED is most compared with Azure Data Factory, SSIS, Informatica PowerCenter, Matillion ETL and Denodo.
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We monitor all Data Integration 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.