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."This solution provides a clear and convenient syntax for our analytical tasks."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The fault tolerant feature is provided."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"Apache Spark can do large volume interactive data analysis."
"Apache Spark provides a very high-quality implementation of distributed data processing."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"The most valuable feature of Apache Spark is its flexibility."
"It's easy to use, and the Hana Studio is pretty good."
"It is very stable and very innovative. You can integrate many applications with it."
"Using this solution has given us better details for reporting and analytics."
"It's stable and reliable."
"The solution offers advanced features that the company was struggling to implement."
"If you want to scale with new processes and new reports, that's fairly easy."
"Eases management of databases."
"It is very flexible to integrate with SaaS components."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"The graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate."
"It's not easy to install."
"The product could improve the user interface and make it easier for new users."
"When using Spark, users may need to write their own parallelization logic, which requires additional effort and expertise."
"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."
"It should support more programming languages."
"Apache Spark can improve the use case scenarios from the website. There is not any information on how you can use the solution across the relational databases toward multiple databases."
"The initial setup was very, very complex, tedious, and costly and required someone with great expertise to complete it."
"The surface side or Attack dashboard needs improvement because there are some gaps after sales services."
"The performance and integration with other products are areas in need of improvement."
"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."
"When you do a report on a non-SAP platform, you face some compatibility problems."
"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."
"SAP HANA is not perfect and they could improve by having more options and more integration."
"They should develop and improve the solution's data management system."
Apache Spark is ranked 1st in Hadoop with 60 reviews while SAP HANA is ranked 1st in Embedded Database with 81 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 Azure Stream Analytics, 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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