We performed a comparison between IBM InfoSphere DataStage and StreamSets 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 most valuable feature is the product's versatility to inject data."
"When we have needed help from the IBM team, they were helpful. Our company is a premium partner so we get fast responses."
"It is quite useful and powerful."
"The most valuable feature is the ability to transfer information via notes."
"The solution is stable."
"The concept of integration is a valuable feature of the product."
"The product is easy to deploy."
"Compared to other ETL tools, DataStage has excellent debugging and development capabilities. And the availability of connectors, even though we sometimes have to opt for specific ones. Also, the availability of patches is good."
"The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."
"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."
"It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution."
"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."
"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."
"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source systems."
"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."
"StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."
"DataStage is quite expensive. It is too hard to find a consultant using DataStage in Turkey."
"Reduced cost would allow more customers to choose the product. It's quite expensive in relation to the cost of other similar solutions."
"The error messaging needs to be improved."
"The graphical user interface (GUI) feels a lot like the interfaces from the 1980s."
"The initial setup can be complex."
"I'd like to be able to do more with the data and metadata, including copy and pasting, et cetera."
"The interface needs improvement. It is really too technical. That is the main problem."
"I really like this tool, but the administration should be on the same client application because a lot of administration features are not on the client-side, and they usually need to have administrative access. It's quite complicated to force IT teams to have separate administrative access from the developers."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."
"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."
"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."
"Visualization and monitoring need to be improved and refined."
"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."
IBM InfoSphere DataStage is ranked 7th in Data Integration with 37 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. IBM InfoSphere DataStage is rated 7.8, while StreamSets is rated 8.4. 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 StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". IBM InfoSphere DataStage is most compared with SSIS, IBM Cloud Pak for Data, Azure Data Factory, Talend Open Studio and Alteryx Designer, whereas StreamSets is most compared with Fivetran, Informatica PowerCenter, Azure Data Factory, SSIS and webMethods.io Integration. See our IBM InfoSphere DataStage vs. StreamSets report.
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