We performed a comparison between SAS Data Management and Spring Cloud Data Flow based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The product offers very good flexibility."
"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."
"I am impressed with the tool's ability to customize."
"This is an established product with powerful data analysis and varied options for user entry points."
"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."
"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."
"If you compare it to SQL, the memory and development times are very quick."
"The tool is reliable, quick, and powerful."
"The most valuable feature is real-time streaming."
"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."
"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."
"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."
"I would like the tool to include the ability to automate the modifications of the integrations."
"The solution could use better documentation."
"The solution is quite expensive and hard to install/configure."
"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place."
"The pricing of the solution needs to be improved. They need to work to make it more affordable."
"With SAS Data Management, you have to purchase an external driver, configure all of the tables for all of the data that you will extract from Salesforce. It's not a straightforward process."
"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."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"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."
SAS Data Management is ranked 43rd in Data Integration with 15 reviews while Spring Cloud Data Flow is ranked 28th in Data Integration with 5 reviews. SAS Data Management is rated 8.4, while Spring Cloud Data Flow is rated 8.0. The top reviewer of SAS Data Management writes "A scalable solution with customer support that is responsive and diligent". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". SAS Data Management is most compared with Informatica PowerCenter, Tungsten RPA, Microsoft Purview Data Governance, SSIS and IBM InfoSphere DataStage, 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 SAS Data Management vs. Spring Cloud Data Flow report.
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