Apache Spark vs Spring MVC comparison

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Executive Summary

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.
To learn more, read our detailed Apache Spark vs. Spring MVC Report (Updated: November 2022).
653,522 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The solution has been very stable.""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.""It is useful for handling large amounts of data. It is very useful for scientific purposes.""There's a lot of functionality.""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.""Apache Spark can do large volume interactive data analysis.""Spark can handle small to huge data and is suitable for any size of company.""One of the key features is that Apache Spark is a distributed computing framework. You can help multiple slaves and distribute the workload between them."

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"The most valuable feature of Spring MVC is the configuration, such as WAF.""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 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.""The solution is open-source and free to use.""We appreciate that this product is really easy to integrate with third-party UI services."

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Cons
"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.""When you are working with large, complex tasks, the garbage collection process is slow and affects performance.""It's not easy to install.""We are building our own queries on Spark, and it can be improved in terms of query handling.""Spark could be improved by adding support for other open-source storage layers than Delta Lake.""This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed.""The logging for the observability platform could be better.""The initial setup was not easy."

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"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.""It can be difficult for a basic user to understand the concepts in this solution, such as inversion of control.""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."

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Pricing and Cost Advice
  • "Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."
  • "Spark is an open-source solution, so there are no licensing costs."
  • "Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
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  • "The solution is free."
  • "Spring MVC is open source and free."
  • "This is an open-source solution, so there are no license costs involved with using it."
  • More Spring MVC Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:I don't think using Apache Spark without Hadoop has any major drawbacks or issues. I have used Apache Spark quite successfully with AWS S3 on many projects which are batch based. Yes for very high… more »
    Top Answer:It's an open-source product. I don't know much about the licensing aspect.
    Top Answer:The interface is the solution's most valuable aspect.
    Top Answer:The cost is quite high. We're using AWS cloud and we find that it's very expensive on it. We're actually looking to see if we can find a solution that's not as expensive as AWS.
    Top Answer:It is a little bit complicated and heavy. It should be more simple and light.
    Ranking
    2nd
    out of 11 in Java Frameworks
    Views
    11,211
    Comparisons
    8,900
    Reviews
    12
    Average Words per Review
    393
    Rating
    8.1
    4th
    out of 11 in Java Frameworks
    Views
    1,619
    Comparisons
    1,173
    Reviews
    4
    Average Words per Review
    394
    Rating
    7.8
    Comparisons
    Also Known As
    Spring by Pivotal, Spring, Spring Framework
    Learn More
    Overview

    Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

    Spring MVC is a Java web framework built on the Servlet API and has been included in the Spring Framework from the very beginning.  It handles web applications that use server-rendered HTML user interface, REST APIs, and much more.  The documentation includes Spring MVCView TechnologiesCORS Support, and WebSocket Support

    For baseline information and compatibility with Servlet container and Java EE version ranges please visit the Spring Framework Wiki.

    Offer
    Learn more about Apache Spark
    Learn more about Spring MVC
    Sample Customers
    NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
    EMC, Aridhia, CoreLogic, CenturyLink, Humana, Purdue University, Tampon Run, ArtsPool, Charity Water, Center for ReSource Conservation, Manos Teatrales
    Top Industries
    REVIEWERS
    Computer Software Company29%
    Financial Services Firm29%
    Marketing Services Firm7%
    Non Profit7%
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company17%
    Comms Service Provider12%
    Retailer6%
    VISITORS READING REVIEWS
    Computer Software Company22%
    Comms Service Provider21%
    Financial Services Firm14%
    Government8%
    Company Size
    REVIEWERS
    Small Business42%
    Midsize Enterprise23%
    Large Enterprise35%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise12%
    Large Enterprise73%
    REVIEWERS
    Small Business30%
    Midsize Enterprise10%
    Large Enterprise60%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise16%
    Large Enterprise63%
    Buyer's Guide
    Apache Spark vs. Spring MVC
    November 2022
    Find out what your peers are saying about Apache Spark vs. Spring MVC and other solutions. Updated: November 2022.
    653,522 professionals have used our research since 2012.

    Apache Spark is ranked 2nd in Java Frameworks with 12 reviews while Spring MVC is ranked 4th in Java Frameworks with 5 reviews. Apache Spark is rated 8.0, while Spring MVC is rated 8.0. 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 "Made our web app development easier with lots of boilerplate code and good community support". Apache Spark is most compared with Spring Boot, Azure Stream Analytics, AWS Batch, AWS Lambda and SAP HANA, whereas Spring MVC is most compared with Jakarta EE, Oracle Application Development Framework, Spring Boot, Vert.x and Open Liberty. See our Apache Spark vs. Spring MVC report.

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    We monitor all Java Frameworks reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.