"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."
"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."
"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."
"The most important feature is that it can help you do the multi-threading concepts."
"The most valuable feature of this solution would be ease of use."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"Its integrability with the rest of the activities on Azure is most valuable."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."
"It's on the cloud, so it's scalable and quite easy to work with."
"Having a single vendor supporting the entire suite of applications."
"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."
"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."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"There is no built-in pipeline exit activity when encountering an error."
"The one element of the solution that we have used and could be improved is the user interface."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"It's lacking a lot of mapping features that Oracle OSB and SOA have. It needs to evolve a lot."
"This is an expensive solution compared to other products on the market."
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.
Create, schedule, and manage your data integration at scale with Azure Data Factory - a hybrid data integration (ETL) service. Work with data wherever it lives, in the cloud or on-premises, with enterprise-grade security.
Oracle Data Integrator Cloud Service provides pushdown data processing; high performance ETL with less data movement which is best for the Cloud. Oracle Data Integrator Cloud Service executes data transformations where the data lies without having to copy data unnecessarily to remote locations.
Azure Data Factory is ranked 2nd in Data Integration Tools with 33 reviews while Oracle Data Integrator Cloud Service is ranked 20th in Cloud Data Integration with 2 reviews. Azure Data Factory is rated 7.8, while Oracle Data Integrator Cloud Service is rated 7.6. The top reviewer of Azure Data Factory writes "There's the good, the bad and the ugly....unfortunately lots of ugly". On the other hand, the top reviewer of Oracle Data Integrator Cloud Service writes "A well-established product that meets all our specifications in terms of usability". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Talend Open Studio, Alteryx Designer and Microsoft Azure Synapse Analytics, whereas Oracle Data Integrator Cloud Service is most compared with Informatica Cloud Data Integration, IBM InfoSphere DataStage and BMC Data Management for IMS and DB2 on zOS.
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