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 main feature that we find valuable is that it is very fast."
"ETL and streaming capabilities."
"I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"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."
"The most valuable feature of this solution is its capacity for processing large amounts of data."
"The deployment of the product is easy."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The most valuable feature is simplicity."
"We appreciate that this product is really easy to integrate with third-party UI services."
"Spring MVC's extensive documentation is the most valuable feature."
"We have found Spring is easy to use and learn."
"Spring MVC is fast and reliable."
"When we shifted from our legacy frameworks to the Spring framework, we discovered that Spring definitely made our development easier. One good example is that there is a lot of boiler plate code available that you don't have to write from scratch, making the development of web applications a much simpler process."
"The solution can scale."
"The best feature of Spring MVC is its auto-configuration capabilities."
"Dynamic DataFrame options are not yet available."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"The solution’s integration with other platforms should be improved."
"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."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"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 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."
"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 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."
"It can be difficult for a basic user to understand the concepts in this solution, such as inversion of control."
"We would like the deployment of this solution to be easier as, at present, it is quite complicated."
"The documentation for Spring MVC could improve."
"I have recently had problems with the changes that were made using Spring Security."
"Spring MVC could improve the integration with DevOps and other applications."
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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