"It is really easy to set up and the interface is easy to use."
"In StreamSets, everything is in one place."
"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."
"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."
"The compare feature is the most valuable piece of it."
"It is not like a traditional ETL, but it gives quite a lot of flexibility."
"Its arrays are powerful enough to handle migrations even when the replication is happening in the background, without causing any trouble with the ongoing traffic."
"The most valuable feature is the data integration for data warehousing."
"As a data integration platform, it is easy to use. It is quite robust and useful for volumetric analysis when you have huge volumes of data. We have tested it for up to ten million rows, and it is robust enough to process ten million rows internally with its parallel processing. Its error logging mechanism is far simpler and easier to understand than other data integration tools. The newer version of InfoSphere has the data catalog and IDC lineage. They are helpful in the easy traceability of columns and tables."
"The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms"
"We are mostly using transmission rules. It has a lot of functions and logic related to transmission. It is a user-friendly tool with in-built functions."
"The Hierarchical Data Stage is good."
"It's a robust solution."
"Once you have Infosphere up and running properly, it is stable."
"It is quite useful and powerful."
"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."
"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."
"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."
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
"HVR Software's technical support could be improved. Whenever we log a case, the response that we get from the support is a bit delayed."
"The documentation can be laid out better to make it easier to find things, and I really wish there was built-in support for changing passwords. Some features don't work as advertised for the platform/repository database, and HVR is not always the fastest at getting results."
"It should have a few more monitoring functionalities."
"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."
"Currently lacking virtualization ability."
"The initial setup could be more straightforward."
"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."
"The response time from support is slow and needs to be improved."
"The setup is extremely difficult."
"In the future, I would like to see more integration with cloud technologies."
"It would be useful to provide support for Python, AR, and Java."
StreamSets offers an end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power the modern data ecosystem and hybrid integration.
Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps.
With StreamSets, you can deliver the continuous data that drives the connected enterprise.
HVR Software is ranked 24th in Data Integration Tools with 3 reviews while IBM InfoSphere DataStage is ranked 9th in Data Integration Tools with 9 reviews. HVR Software is rated 8.6, while IBM InfoSphere DataStage is rated 7.6. The top reviewer of HVR Software writes "Good stability and scalability, easy setup, and valuable compare feature". On the other hand, the top reviewer of IBM InfoSphere DataStage writes "Robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data". HVR Software is most compared with Oracle GoldenGate, Qlik Replicate, AWS Database Migration Service, Matillion ETL and Informatica Cloud Data Integration, whereas IBM InfoSphere DataStage is most compared with SSIS, Talend Open Studio, AWS Glue, Informatica PowerCenter and Azure Data Factory. See our HVR Software vs. IBM InfoSphere DataStage report.
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