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 crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"I feel the streaming is its best feature."
"The main feature that we find valuable is that it is very fast."
"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."
"The most valuable feature of Apache Spark is its ease of use."
"There's a lot of functionality."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The solution is very stable."
"It provides the best documentation for technical support."
"Spring MVC's extensive documentation is the most valuable feature."
"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."
"Spring MVC is fast and reliable."
"Spring has a speedy development process with a lightweight framework."
"The solution is open-source and free to use."
"We appreciate that this product is really easy to integrate with third-party UI services."
"The most valuable feature of Spring MVC is the configuration, such as WAF."
"It requires overcoming a significant learning curve due to its robust and feature-rich nature."
"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's GUI and scalability could be improved."
"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"The solution must improve its performance."
"There were some problems related to the product's compatibility with a few Python libraries."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"The solution could be simplified quite a bit. It's unnecessarily complicated in some areas."
"We would like the deployment of this solution to be easier as, at present, it is quite complicated."
"The initial setup could be more straightforward."
"Spring IDE needs some work and improvement. We have faced many issues when adding third-party Eclipse plugins."
"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."
"The newer versions of Spring MVC have released a lot of features that we are not using right now because, in many cases, we are limited to running older versions. As such, it would be nice if Spring were to improve support for upgrading to newer versions, especially for legacy applications."
"I saw some error messages coming up when they were getting problems actually viewing all the reports."
"I have recently had problems with the changes that were made using Spring Security."
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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