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 crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"Apache Spark can do large volume interactive data analysis."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"It provides a scalable machine learning library."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"The processing time is very much improved over the data warehouse solution that we were using."
"Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica. Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"This is a feature-rich product and I like all of them."
"The solution is marvelous because it controls everything including workflow and that makes our company more productive."
"When we upgraded, we received more functions or more features."
"The solution is extremely stable. That's the most important aspect of the solution, for our organization. There is no downtime, and the performance is very good."
"What I like best about SAP HANA is that it's faster than Microsoft SQL Server."
"The UX experience is very good."
"It's very convenient and very innovative."
"The feature that I like the most is that we can transport the data to our web data application. SAP HANA's performance is really perfect. We're working on big data, and SAP HANA is really working on high performance. We are happy working with it."
"There were some problems related to the product's compatibility with a few Python libraries."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."
"The solution needs to optimize shuffling between workers."
"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."
"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"Its UI can be better. Maintaining the history server is a little cumbersome, and it should be improved. I had issues while looking at the historical tags, which sometimes created problems. You have to separately create a history server and run it. Such things can be made easier. Instead of separately installing the history server, it can be made a part of the whole setup so that whenever you set it up, it becomes available."
"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."
"The openness of the system could be more developed. The solution should go into the cloud. The cloud mechanism should be more invested."
"I would have rated the solution higher if this version was not missing some key features the newer version has."
"Needs graphical programming without coding."
"If the developers were to enhance or improve the application logic while processing the transactions, that would be great."
"The solution is very expensive, however. The pricing depends on the number of users and many other factors that affect licensing."
"I think that the pricing is high and it needs improvement."
"The user interface and CRM need to be more user-friendly."
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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