"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 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."
"In StreamSets, everything is in one place."
"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."
"It is really easy to set up and the interface is easy to use."
"The basic functionality is quite good as is the basic logic and data information."
"Its integration capabilities and the data migration capabilities are the most valuable. It is very good for SAP and non-SAP tools. It has very good integration with SAP, but it also has the capabilities to connect to other systems. We find it very helpful and stable."
"Data Services' table comparison mechanism is very powerful. It's pretty hard to find a similar feature in other solutions."
"You can always manipulate a lot of things as long as you have the skill level."
"We can extract data at a table level, extract data at the ETL level, and we can extract data at an ODP level."
"The most valuable feature is the ETL functionality."
"I like how SAP Data Services links reporting and data integration. That's what's most interesting. You also have the opportunity to leverage the power of the Data Services server."
"I appreciate having access to the SAP data."
"The installation process is easy."
"It's a consolidated product. It works and it does its job pretty well."
"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."
"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."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"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."
"Source code control is another headache. When your source code base gets too large, managing the source code becomes cumbersome."
"The migration of the solution between different environments is quite complex."
"They could make it easier to work with web services."
"It would be nice if this solution was a bit easier to move from development to production."
"The skillset of data engineers matters a bit to use all the functionality of this solution. Otherwise, the delivery speed won't be faster."
"I want some more business intelligence applications. People need to know more and more about data, including the transformation rules, etc. Informatica is a better product for data cataloging. SAP should update the data catalog."
"It's an ETL that is very good with relational databases but not as good with files and semi-structured files."
"Data Services SAP is lacking in sources and target databases compared to Informatica. SAP Data Services should have more connectivity."
"The setup can be difficult for those not familiar with the solution."
"The customization can be a bit difficult."
SAP Data Services is ranked 8th in Data Integration Tools with 9 reviews while WSO2 Enterprise Integrator is ranked 21st in Data Integration Tools with 3 reviews. SAP Data Services is rated 8.0, while WSO2 Enterprise Integrator is rated 9.0. The top reviewer of SAP Data Services writes "It's a powerful tool that does a lot, but it has its annoyances". On the other hand, the top reviewer of WSO2 Enterprise Integrator writes "Customizable, with good pricing and a good interface". SAP Data Services is most compared with Azure Data Factory, SSIS, Informatica PowerCenter, SAP Process Orchestration and Palantir Foundry, whereas WSO2 Enterprise Integrator is most compared with Red Hat Fuse, IBM Integration Bus, Mule ESB, Spring Cloud Data Flow and webMethods Integration Server. See our SAP Data Services vs. WSO2 Enterprise Integrator report.
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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.
