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."With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"Apache Spark provides a very high-quality implementation of distributed data processing."
"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."
"It is highly scalable, allowing you to efficiently work with extensive datasets that might be problematic to handle using traditional tools that are memory-constrained."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"The solution has been very stable."
"The product is useful for analytics."
"Apache Spark can do large volume interactive data analysis."
"Spring has a speedy development process with a lightweight framework."
"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."
"The interface is the solution's most valuable aspect."
"The solution can scale."
"We have found Spring is easy to use and learn."
"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."
"We appreciate that this product is really easy to integrate with third-party UI services."
"The solution is open-source and free to use."
"It requires overcoming a significant learning curve due to its robust and feature-rich nature."
"In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, do the transformation in a subsecond, and all that."
"The migration of data between different versions could be improved."
"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."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"The logging for the observability platform could be better."
"Apache Spark should add some resource management improvements to the algorithms."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"I have recently had problems with the changes that were made using Spring Security."
"I saw some error messages coming up when they were getting problems actually viewing all the reports."
"The initial setup could be more straightforward."
"Adding more modules takes about 10 to 15 minutes each. It would be nice if they could reduce that part. The deployment time is a little high."
"Spring IDE needs some work and improvement. We have faced many issues when adding third-party Eclipse plugins."
"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."
"Spring MVC could improve the integration with DevOps and other applications."
"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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