"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."
"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."
"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."
"In StreamSets, everything is in one place."
"It is really easy to set up and the interface is easy to use."
"The pricing of the solution is quite good."
"It is stable and scalable."
"The OCR was quite stable and flexible."
"Provides valuable tools working in integration with RPA tools."
"The most valuable features are workflow and process automation."
"The ability to script information from websites is most valuable. It also seems to be fairly robust and reasonably easy to manage on a server-based deployment. We have a number of robots operating on the central server."
"The flexibility to use already-developed components is really good. You can use it for Excel-related operations and other things."
"I like that it is a very good integration tool with many other things. TIBCO is very good for cloud integration"
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
"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."
"We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"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."
"The product needs more AI capabilities."
"There is really nothing special about the capabilities of this product."
"The solution could use some AI integrated features."
"The interface could be better from a usability standpoint."
"Exception handling needs to be improved."
"Its documentation is not widely available on the web. They should work on the availability of its documentation. In Automation Anywhere, there is a feature called Discovery Bot that automatically records the process steps and suggests a possible bot. I am not sure if such a feature is available in Kofax. If it is not available, it will be very good to have this feature. "
"The process discovery could be a bit better."
"We are on version 10.6, and the current version seems to be 11. Kofax is cycling the capabilities of the product very quickly. One of the difficulties has been to actually keep up with the capabilities as they've evolved. On the one hand, it is good that the product is getting better, but on the other hand, it is difficult to implement the best way with a product that is evolving constantly."
"Integrations could be better. Although integration is good, we have faced some block issues."
Kofax RPA is ranked 12th in Robotic Process Automation (RPA) with 7 reviews while TIBCO Cloud Integration is ranked 14th in Integration Platform as a Service (iPaaS) with 1 review. Kofax RPA is rated 7.4, while TIBCO Cloud Integration is rated 8.0. The top reviewer of Kofax RPA writes "Stable, scalable, and provides flexibility to use already-developed components, but its documentation is not widely available and it needs a feature similar to Discovery Bot". On the other hand, the top reviewer of TIBCO Cloud Integration writes "A very good cloud integration tool with many other things". Kofax RPA is most compared with UiPath, ABBYY FlexiCapture, Blue Prism, Microsoft Power Automate and Automation Anywhere (AA), whereas TIBCO Cloud Integration is most compared with SAP Process Orchestration, Microsoft Azure Logic Apps, Axway AMPLIFY Application Integration, Oracle Integration Cloud Service and Azure Data Factory.
See our list of best Data Integration Tools vendors.
We monitor all Data Integration Tools reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
