We performed a comparison between Informatica Cloud Data Integration and StreamSets based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It has a more UI-based tool, and the scripting is good."
"It is quite easy to use and flexible."
"Their new licensing is very flexible. With Informatica Cloud, you have plenty of items under the same umbrella, such as services, offerings, data quality, and data masking. You have also got master data management and API management. What I really like about them is that you don't need to go to Informatica and say that you need a data integration module. You would say that you need iPaaS or Informatica Cloud. They'll then try to understand your needs and give you IPUs, which are the processing units. If I purchased a hundred IPUs from Informatica as a customer, I can use 70 IPUs for data integration. I would also need data quality, so I can use 10 IPUs for data quality. I can use the remaining 20 IPUs for API management. Down the line, if I see that my initial data integration needs for the development phase are met, then out of the 70 IPUs assigned for data integration, I can use 30 IPUs for data masking. I can shuffle these numbers in any way within the Informatica Cloud umbrella for the tenure for which I have subscribed to these IPUs. I can use all services the way I want. This flexibility is what I really love about Informatica. It also has got good connectors."
"Whether we need data cleansing or data mastering, we get it all in one platform."
"The most valuable features of Informatica Cloud Data Integration for our clients are the AI capabilities within Informatica Intelligent Cloud Services."
"The solution provides increased efficiency while still being user-friendly and easy to operate."
"The mass ingestion functionality and the elasticity of the solution are great."
"The Mapping Designer allows for declarative ETL development (visual scripting) that leverages a wide array of different transformations."
"The most valuable feature is the pipelines because they enable us to pull in and push out data from different sources and to manipulate and clean things up within them."
"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."
"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."
"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."
"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."
"In StreamSets, everything is in one place."
"The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."
"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 could be improved by including a buffer that saves data when there is a connectivity issue."
"There may be some types of limitations with the performance."
"There is room for improvement at the highest level in terms of useability and connectors for various types of new applications. The row processing performance could be better because you experience some latency dealing with high volumes of data. Most organizations will be dealing with multiple cloud applications, so you could see performance issues moving from one system to another."
"Error reporting and debugging need improvement."
"I have received feedback from certain teams and there is a steep learning curve to use this solution."
"The cloud version of the Informatica, it's a very substandard product. They might say it's enterprise-ready but it's not at all ready. They need to add more features, such as improved data replication features. If you look at other tools, such as Matillion they are now cloud-native and flexible. Additionally, Informatica Cloud Data Integration should have a good migration strategy from Informatica PowerCenter to Informatica Cloud Data Integration."
"I would like to see more functionality added so that it is a bit closer to how much you can do with Informatica PowerCenter."
"The error information provided is not informative, as compared to Power Center."
"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."
"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."
"I would like to see further improvement in the UI. In addition, upgrades are not automatic and they should be automated. Currently, we have to manually upgrade versions."
"Sometimes, when we have large amounts of data that is very efficiently stored in Hadoop or Kafka, it is not very efficient to run it through StreamSets, due to the lack of efficiency or the resources that StreamSets is using."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"Using ETL pipelines is a bit complicated and requires some technical aid."
"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."
"Visualization and monitoring need to be improved and refined."
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Informatica Cloud Data Integration is ranked 5th in Cloud Data Integration with 40 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Informatica Cloud Data Integration is rated 7.8, while StreamSets is rated 8.4. The top reviewer of Informatica Cloud Data Integration writes "A stable, scalable, and user-friendly solution". 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 Cloud Data Integration is most compared with Informatica PowerCenter, Azure Data Factory, AWS Glue, Fivetran and Mule Anypoint Platform, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage. See our Informatica Cloud Data Integration vs. StreamSets report.
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