We performed a comparison between Informatica Data Integration Hub and StreamSets 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."The MDM solution is capable of integrating multiple systems, so it helped us to solve the purpose of centralizing the depository as well as the standardization of mass data. It takes away all the ambiguity around data integrity issues or all the process challenges which happen when every stage of a process uses a different source as master data."
"Performance and flexibility-wise, they're very user-friendly."
"The technical support services are good."
"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."
"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."
"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"
"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."
"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."
"The UI is user-friendly, it doesn't require any technical know-how and we can navigate to social media or use it more easily."
"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."
"The initial setup was not very straightforward. Not complex, but not very simple either."
"They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently."
"When it comes to UI look and feel and user experience, Informatica is not as good as other solutions."
"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 data collector in StreamSets has to be designed properly. For example, a simple database configuration with MySQL DB requires the MySQL Connector to be installed."
"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."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"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."
"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."
"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."
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Informatica Data Integration Hub is ranked 37th in Data Integration with 3 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Informatica Data Integration Hub is rated 8.0, while StreamSets is rated 8.4. The top reviewer of Informatica Data Integration Hub writes "Excellent at standardizing mass data and capable of integrating with multiple solutions ". On the other hand, the top reviewer of StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". Informatica Data Integration Hub is most compared with Informatica PowerCenter, AWS Database Migration Service, Azure Data Factory, SAP Data Hub and Mule Anypoint Platform, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage. See our Informatica Data Integration Hub vs. StreamSets report.
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