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 provides a scalable machine learning library."
"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."
"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."
"Apache Spark can do large volume interactive data analysis."
"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."
"One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast."
"Provides a lot of good documentation compared to other solutions."
"The processing time is very much improved over the data warehouse solution that we were using."
"We have found Spring is easy to use and learn."
"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 MVC is fast and reliable."
"The best feature of Spring MVC is its auto-configuration capabilities."
"The interface is the solution's most valuable aspect."
"The most valuable feature of Spring MVC is the configuration, such as WAF."
"The solution can scale."
"Spring has a speedy development process with a lightweight framework."
"There were some problems related to the product's compatibility with a few Python libraries."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."
"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."
"Spark could be improved by adding support for other open-source storage layers than Delta Lake."
"Apache Spark can improve the use case scenarios from the website. There is not any information on how you can use the solution across the relational databases toward multiple databases."
"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"It could provide faster performance."
"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 solution could be simplified quite a bit. It's unnecessarily complicated in some areas."
"Spring MVC could improve the integration with DevOps and other applications."
"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."
"The initial setup could be more straightforward."
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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