We performed a comparison between IBM Cloud Pak for Integration and StreamSets based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Cloud Pak for Integration is definitely scalable. That is the most important criteria."
"The most preferable aspect would be the elimination of the command, which was a significant improvement. In the past, it was a challenge, but now we can proceed smoothly with the implementation of our policies and everything is managed through JCP. It's still among the positive aspects, and it's a valuable feature."
"It is a stable solution."
"The most valuable aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."
"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."
"The entire user interface is very simple and the simplicity of creating pipelines is something that I like very much about it. The design experience is very smooth."
"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."
"It's very easy to integrate. It integrates with Snowflake, AWS, Google Cloud, and Azure. It's very helpful for DevOps, DataOps, and data engineering because it provides a comprehensive solution, and it's not complicated."
"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."
"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."
"I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks."
"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."
"The initial setup is not easy."
"The pricing can be improved."
"Its queuing and messaging features need improvement."
"Setting up Cloud Pak for Integration is relatively complex. It's not as easy because it has not yet been fully integrated. You still have some products that are still not containerized, so you still have to run them on a dedicated VM."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."
"Using ETL pipelines is a bit complicated and requires some technical aid."
"Visualization and monitoring need to be improved and refined."
"The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."
"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."
"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
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IBM Cloud Pak for Integration is ranked 14th in Cloud Data Integration with 4 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. IBM Cloud Pak for Integration is rated 8.6, while StreamSets is rated 8.4. The top reviewer of IBM Cloud Pak for Integration writes "A hybrid integration platform that applies the functionality of closed-loop AI automation". On the other hand, the top reviewer of StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". IBM Cloud Pak for Integration is most compared with IBM App Connect, IBM API Connect, IBM DataPower Gateway, MuleSoft Anypoint API Manager and Microsoft Azure API Management, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and Oracle GoldenGate. See our IBM Cloud Pak for Integration vs. StreamSets report.
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