We performed a comparison between Apache Spark and SAP HANA based on real PeerSpot user reviews.
Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."
"The deployment of the product is easy."
"This solution provides a clear and convenient syntax for our analytical tasks."
"The most valuable feature of this solution is its capacity for processing large amounts of data."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"The most valuable feature of Apache Spark is its flexibility."
"We can save data very easily."
"It's stable and reliable."
"We have found the solution to be customizable and it is beneficial it comes as a bundled package. Additionally, it is user-friendly."
"The solution is stable."
"The feature I found most valuable in SAP HANA is modeling. I also like that the solution has good integration and you can integrate it with any system, even third-party systems."
"The most value for us was in terms of using it to issue tenders online. We host our server, but it is open to the public, so clients who want to buy those tenders were able to go online, put their tender documents up, and we could evaluate them using SAP."
"In comparison with other DMS solutions, it offers good performance."
"The data storage requirement is reduced from the original database to the HANA database."
"One limitation is that not all machine learning libraries and models support it."
"The logging for the observability platform could be better."
"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."
"Spark could be improved by adding support for other open-source storage layers than Delta Lake."
"They could improve the issues related to programming language for the platform."
"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it."
"It's a complex initial setup."
"The surface side or Attack dashboard needs improvement because there are some gaps after sales services."
"The bid process needs to be improved."
"I'd just like to see some more improvements done on the training, both on the functional training and technical training sides as a part of the complete solution."
"The interface is a little bit hard to customize. You almost have to consult the SAP original developer to change it."
"In my limited experience using SAP, the process of granting access to different modules is difficult. Specifically, the requirement to assign roles and key codes to users rather than being able to assign them individually made the process more complex. It would be beneficial if there was a way to assign key codes separately, rather than having to create multiple roles. This would make managing access easier."
"The product is very demanding on memory requirements."
"The challenge right now is all databases are on S4 HANA architecture. You're running it for HANA, but not all the functionalities are available. If they can speed up getting all the databases on S4 HANA that would help."
Apache Spark is ranked 1st in Hadoop with 60 reviews while SAP HANA is ranked 1st in Embedded Database with 79 reviews. Apache Spark is rated 8.4, while SAP HANA is rated 8.4. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of SAP HANA writes "Excellent compatibility between modules and the control". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, Cloudera Distribution for Hadoop and AWS Lambda, whereas SAP HANA is most compared with Oracle Database, SQL Server, MySQL, IBM Db2 Database and SAP Adaptive Server Enterprise. See our Apache Spark vs. SAP HANA report.
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