We performed a comparison between Apache Spark and Spring MVC based on real PeerSpot user reviews.
Find out in this report how the two Java Frameworks solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of Apache Spark is its memory processing because it processes data over RAM rather than disk, which is much more efficient and fast."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly."
"Spark can handle small to huge data and is suitable for any size of company."
"Apache Spark can do large volume interactive data analysis."
"The product is useful for analytics."
"I found the solution stable. We haven't had any problems with it."
"The processing time is very much improved over the data warehouse solution that we were using."
"We appreciate that this product is really easy to integrate with third-party UI services."
"Spring gives you the opportunity to develop architecture in the simplest way possible. It comes with everything you would want in terms of security. If you want to access the database, you have the ability to do that."
"It provides the best documentation for technical support."
"Spring has a speedy development process with a lightweight framework."
"Dependency Injection is one of the major features which makes our life easier using Spring. It is well documented and has active communities, which provide us enormous help."
"The most valuable features of Spring MVC are the modules, such as Spring Admin. All the Spring solutions work well together and are simple to maintain, such as the load balancing on the client side."
"Spring MVC is fast and reliable."
"The solution can scale."
"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"The initial setup was not easy."
"The setup I worked on was really complex."
"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."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"Dynamic DataFrame options are not yet available."
"Apache Spark provides very good performance The tuning phase is still tricky."
"I expect the solution to offer and include a lot of packages so that it can be configured more easily or the speed level increases, thereby helping it overcome its shortcomings."
"Spring MVC could improve the integration with DevOps and other applications."
"The documentation for Spring MVC could improve."
"I have recently had problems with the changes that were made using Spring Security."
"Spring IDE needs some work and improvement. We have faced many issues when adding third-party Eclipse plugins."
"The solution could be simplified quite a bit. It's unnecessarily complicated in some areas."
"I saw some error messages coming up when they were getting problems actually viewing all the reports."
"It could provide faster performance."
Apache Spark is ranked 2nd in Java Frameworks with 60 reviews while Spring MVC is ranked 3rd in Java Frameworks with 16 reviews. Apache Spark is rated 8.4, while Spring MVC 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 Spring MVC writes "Straightforward setup, highly stable, and useful online support". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas Spring MVC is most compared with Jakarta EE, Spring Boot, Open Liberty, Oracle Application Development Framework and Vert.x. See our Apache Spark vs. Spring MVC report.
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