We performed a comparison between SAP Analytics 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."Data consistency is also a notable feature; the system takes care of data consistency, so you don't need to handle it manually."
"For report scheduling, I always prefer SAP because it has the most powerful scheduling features, like sending reports to more than 1,000 customers per day. That option is not as good in Microsoft BI and in Tableau it only exists as an add-on option."
"SAP Analytics Hub offers a user-friendly interface with effortless configuration, seamless updates, and real-time availability of information. It avoids the complexities associated with batch processing, providing a smooth and efficient experience."
"What I like best about this solution is that it is built into the SAP line, making it easier to integrate with other SAP products."
"This product provides good reports using a single pane of glass."
"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."
"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 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."
"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."
"It's very easy to integrate. It integrates with Snowflake, AWS, Google Cloud, and Azure. It's very helpful for DevOps, DataOps, and data engineering because it provides a comprehensive solution, and it's not complicated."
"In StreamSets, everything is in one place."
"It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution."
"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"
"The technical support for Analytics Hub is limited and could be improved."
"The interface can be simplified because it is not a user-friendly experience."
"The analytics part of SAP has not been that good up until now. They're still in the infant stage and development is still going on. SAP has some cloud analytics and they're trying to configure it in Lumira, but it's not that good at this point."
"Pricing and support are integrated into the system. However, the support process can be challenging, particularly when navigating the SAP support site, which lacks user-friendliness and ease of access."
"Faster implementation of new functions for the new product is an area of improvement in SAP Analytics Hub."
"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."
"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."
"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."
"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."
"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."
"Using ETL pipelines is a bit complicated and requires some technical aid."
"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
SAP Analytics Hub is ranked 46th in Data Integration with 6 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. SAP Analytics Hub is rated 7.2, while StreamSets is rated 8.4. The top reviewer of SAP Analytics Hub writes "Powerful capabilities for cross-functional reporting and dashboard creation, with real-time access". 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". SAP Analytics Hub is most compared with SAP Analytics Cloud, Workday Prism Analytics and Logi Analytics, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage. See our SAP Analytics Hub vs. StreamSets report.
See our list of best Data Integration vendors.
We monitor all Data Integration 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.
