We performed a comparison between Denodo and Spring Cloud Data Flow based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."Denodo's best features are its performance, easy data transformation, and the job scheduler."
"The data abstraction is the most valuable feature."
"While we may not be using all the features of Denodo at this time, we have found the data virtualization features to be very useful in helping us connect our data sources together, bringing all our data into one platform."
"It is easy to virtualize data using the solution."
"Access to numerous forums and internet information."
"The best thing about Denodo is that creating and deploying a web service can be done in about 10 minutes, compared to a whole day when it comes to other solutions (such as when deploying with Java and AWS)."
"It can support a number of data sources, and it can pull flat files, from cloud-based databases or from those on-premises. Denodo can pull from any data source and interface with the view. Then, we can publish the view."
"The most valuable feature is Data Catalogs."
"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 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 is very user-friendly."
"The solution is slow when there are many virtualization layers."
"I would like to see a connectivity option with third-party apps, for example, JDBC, and ODBC drivers. Currently, we need to install it separately from the Denodo side and then connect it."
"The solution should have its own acceleration technology."
"The feature that you have to connect on LDAP needs improvement."
"We occasionally have some integration issues that we need to work through."
"We can't scale it to meet digital requirements."
"Lacks integrations with AWS, GCP and the like."
"There have been some issues when you are at a table. Currently, Denodo exports data sets for a tabular model. When you are finished modeling your database or data warehouse they export a link to be used in Tableau. They should support other tools like Power BI."
"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."
Denodo is ranked 12th in Data Integration with 29 reviews while Spring Cloud Data Flow is ranked 29th in Data Integration with 5 reviews. Denodo is rated 7.8, while Spring Cloud Data Flow is rated 8.0. The top reviewer of Denodo writes "Saves our underwriters' time with data virtualization, but could provide more learning resources". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". Denodo is most compared with Azure Data Factory, AWS Glue, Delphix, Mule Anypoint Platform and Informatica PowerCenter, whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and TIBCO BusinessWorks.
See our list of best Data Integration vendors.
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.
