We performed a comparison between IBM InfoSphere DataStage 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."Highly customizable: Allowing you to handle multiple data latencies (scheduled batch, on-demand, and real-time) in the same job."
"The most valuable feature for our data processing needs is IBM InfoSphere DataStage's capability to handle ETL tasks with large record volumes."
"It is quite useful and powerful."
"The ETL tools are probably the most valuable feature. It has an IBM tool, a friendly UI and it makes things more comfortable."
"The solution's scalability is really good...we are using multi-instance jobs where you can scale them easily."
"I am impressed with the tool's ETL tracing."
"We can view what we want to do. We can transform data and put them on tables."
"The concept of integration is a valuable feature of the product."
"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 feature is real-time streaming."
"The product is very user-friendly."
"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."
"DataStage is quite expensive. It is too hard to find a consultant using DataStage in Turkey."
"What needs improvement in IBM InfoSphere DataStage is its pricing. The pricing for the solution is higher than its competitors, so a lot of the clients my company has worked with prefer other tools over IBM InfoSphere DataStage because of the high price tag. Another area for improvement in the solution stems from a lot of new types of databases, for example, databases in the cloud and big data have become available, and IBM InfoSphere DataStage is working on various connectors for different data sources, but that still isn't up-to-date, meaning that some connectors are missing for modern data sources. The latest version of IBM InfoSphere DataStage also has a complex architecture, so my team faced frequent outages and that should be improved as well."
"It doesn't have any big data connections. It would be good to have them because most of the systems are moving towards big data. There should also be a user-friendly way to interact with the cloud. Its loading process is very slow. It takes a lot of time for around 5 or 6 million records, and we are not able to provide real-time data to the vendors due to this delay. Its performance needs to be improved. It is also like a legacy system. It is not updated much. In higher versions, they only do small changes. We would like to have new features and new technologies."
"Working with some of the big data components is good, but I can see improvements are needed."
"Its documentation is not up to the mark. While building APIs, we had a lot of problems trying to get around it because it is not very user-friendly. We tried to get hold of API documentation, but the documentation is not very well thought out. It should be more structured and elaborate. In terms of additional features, I would like to see good reporting on performance and performance-tuning recommendations that can be based on AI. I would also like to see better data profiling information being reported on InfoSphere."
"Their web interface is good but the on-prem sites are outdated. The solution could also be improved if they could integrate the data pipeline scheduling part of their interface."
"The initial setup could be more straightforward."
"So, there are some features that are missing. If I compare DataStage to Talend, Talend allows you to write custom code in Java or use these tools in your applications as well if you are building a job application. But in DataStage, it does not allow you to write custom code for any component."
"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."
IBM InfoSphere DataStage is ranked 7th in Data Integration with 36 reviews while Spring Cloud Data Flow is ranked 30th in Data Integration with 5 reviews. IBM InfoSphere DataStage is rated 7.8, while Spring Cloud Data Flow is rated 8.0. The top reviewer of IBM InfoSphere DataStage writes "User-friendly with a lot of functions for transmission rules, but has slow performance and not suitable for a huge volume of data". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Good logging mechanisms, a strong infrastructure and pretty scalable". IBM InfoSphere DataStage is most compared with IBM Cloud Pak for Data, SSIS, Azure Data Factory, Talend Open Studio and Informatica PowerCenter, whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and Mule Anypoint Platform.
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