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."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."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The fault tolerant feature is provided."
"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"The solution has been very stable."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"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."
"Features include machine learning, real time streaming, and data processing."
"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."
"Spring has a speedy development process with a lightweight framework."
"The solution is open-source and free to use."
"The most valuable feature of Spring MVC is the configuration, such as WAF."
"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 best feature of Spring MVC is its auto-configuration capabilities."
"Spring MVC is fast and reliable."
"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."
"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 initial setup was not easy."
"At the initial stage, the product provides no container logs to check the activity."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"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."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"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."
"We would like the deployment of this solution to be easier as, at present, it is quite complicated."
"I saw some error messages coming up when they were getting problems actually viewing all the reports."
"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."
"The initial setup could be more straightforward."
"The solution could be simplified quite a bit. It's unnecessarily complicated in some areas."
"I have recently had problems with the changes that were made using Spring Security."
"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."
"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."
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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