We performed a comparison between StreamSets and Tungsten RPA 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."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."
"One of the things I like is the data pipelines. They have a very good design. Implementing pipelines is very straightforward. It doesn't require any technical skill."
"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."
"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."
"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 Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."
"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."
"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."
"Kofax RPA's best feature is its high success percentage in picking up information from documents, especially where the DPI is really low."
"The solution is scalable."
"It is stable and scalable."
"It is very simple and easy to learn compared to any other RPA tools such as UiPath, Automation Anywhere and Blue Prism."
"The OCR was quite stable and flexible."
"You can automate browsing tasks without needing a server connection. The platform provides its browser, allowing you to run anything inside it."
"The pricing of the solution is quite good."
"The product saves time and resources."
"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."
"Sometimes, when we have large amounts of data that is very efficiently stored in Hadoop or Kafka, it is not very efficient to run it through StreamSets, due to the lack of efficiency or the resources that StreamSets is using."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"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."
"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"Using ETL pipelines is a bit complicated and requires some technical aid."
"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."
"The solution could use some AI integrated features."
"Automation with the latest websites is not effective. The support of newer websites developed using new technologies would improve this solution."
"The solution needs to be scalable."
"The interface could be better from a usability standpoint."
"I'd like to see a recording function and a more simple interface."
"The product needs more AI capabilities."
"I would like to see them further enhance the OCR, specifically in the multi-language support."
"The process discovery could be a bit better."
StreamSets is ranked 8th in Data Integration with 24 reviews while Tungsten RPA is ranked 12th in Robotic Process Automation (RPA) with 24 reviews. StreamSets is rated 8.4, while Tungsten RPA is rated 7.4. The top reviewer of StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". On the other hand, the top reviewer of Tungsten RPA writes "A stable product that provides end-to-end solutions for different business problems". StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage, whereas Tungsten RPA is most compared with UiPath, Microsoft Power Automate, Blue Prism, Automation Anywhere (AA) and SAS Data Management. See our StreamSets vs. Tungsten RPA report.
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