Apache Spark vs Spring MVC comparison

Apache and VMware are both solutions in the Java Frameworks category. Apache is ranked #2 with an average rating of 8.6, while VMware is ranked #4 with an average rating of 8.8. Apache holds a 5.5% mindshare in JF, compared to VMware’s 3.1% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 89% of VMware users who would recommend it.

Apache Spark

Read 66 Apache Spark reviews

2,198 Views
1,690 Comparison Views

90% willing to recommend

Spring MVC

Read 16 Spring MVC reviews

1,067 Views
670 Comparison Views

89% willing to recommend

Apache Spark

Spring MVC

Comparison Buyer's Guide

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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: April 2025).

Buyer's Guide

Apache Spark vs. Spring MVC

April 2025

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Helped 849,190 peers since 2012

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Apache Spark

Ranking in Java Frameworks

2nd

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

Ranking in other categories

Hadoop (1st), Compute Service (4th)

Spring MVC

Ranking in Java Frameworks

4th

Average Rating

8.4

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Java Frameworks category, the mindshare of Apache Spark is 5.5%, down from 7.5% compared to the previous year. The mindshare of Spring MVC is 3.1%, up from 2.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Java Frameworks

Featured Reviews

Ilya Afanasyev

Senior Software Development Engineer at Yahoo!

Reliable, able to expand, and handle large amounts of data well

We use batch processing. It works well with our formats and file versions. There's a lot of functionality. In our pipeline each hour, we make a copy of data from MongoDB, of the changes from MongoDB to some specific file. Each time pipeline copied all of the data, it would do it each time without changes to all of the tables. Tables have a lot of data, and in the last MongoDB version, there is a possibility to read only changed data. This reduced the cost and configuration of the cluster, and we saved about $150,000. The solution is scalable. It's a stable product.

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Arkabrata Ghosh

Java developer at Marlabs Inc.

A scalable tool with great auto-configuration capabilities

The best feature of Spring MVC is its auto-configuration capabilities. A user need not configure anything in the product as it offers configuration files to set profiling and guide users with what they need to connect for development, staging, or production. The auto-configuration is one of the best components of the solution.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"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."

"Provides a lot of good documentation compared to other solutions."

"The most valuable feature of this solution is its capacity for processing large amounts of data."

"The scalability has been the most valuable aspect of the solution."

"The solution has been very stable."

"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."

"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."

"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."

More Apache Spark pros

"The most valuable feature is simplicity."

"The interface is the solution's most valuable aspect."

"We have found Spring is easy to use and learn."

"The best feature of Spring MVC is its auto-configuration capabilities."

"The solution is open-source and free to use."

"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."

"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."

"It provides the best documentation for technical support."

More Spring MVC pros

Cons

"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."

"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."

"When you are working with large, complex tasks, the garbage collection process is slow and affects performance."

"There were some problems related to the product's compatibility with a few Python libraries."

"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."

"The Spark solution could improve in scheduling tasks and managing dependencies."

"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."

"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."

More Apache Spark cons

"The documentation for Spring MVC could improve."

"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."

"The solution could be simplified quite a bit. It's unnecessarily complicated in some areas."

"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."

"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."

"I saw some error messages coming up when they were getting problems actually viewing all the reports."

More Spring MVC cons

Pricing and Cost Advice

"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."

"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."

"Apache Spark is an open-source tool."

"We are using the free version of the solution."

"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."

"The product is expensive, considering the setup."

"The tool is an open-source product. If you're using the open-source Apache Spark, no fees are involved at any time. Charges only come into play when using it with other services like Databricks."

"Licensing costs can vary. For instance, when purchasing a virtual machine, you're asked if you want to take advantage of the hybrid benefit or if you prefer the license costs to be included upfront by the cloud service provider, such as Azure. If you choose the hybrid benefit, it indicates you already possess a license for the operating system and wish to avoid additional charges for that specific VM in Azure. This approach allows for a reduction in licensing costs, charging only for the service and associated resources."

More Apache Spark pricing and cost advice

"We are using the open-source version of the solution."

"It is an open-source solution."

"This is an open-source solution, so there are no license costs involved with using it."

"The solution is free."

"Spring MVC is open source and free."

"It is an affordable solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

13%

Manufacturing Company

Comms Service Provider

Financial Services Firm

24%

Computer Software Company

21%

Government

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Apache Spark?

We use Spark to process data from different data sources.

See all answers

What is your experience regarding pricing and costs for Apache Spark?

Compared to other solutions like Doc DB, Spark is more costly due to the need for extensive infrastructure. It requires significant investment in infrastructure, which can be expensive. While cloud...

See all answers

What needs improvement with Apache Spark?

The Spark solution could improve in scheduling tasks and managing dependencies. Spark alone cannot handle sequential tasks, requiring environments like Airflow scheduler or scripts. For instance, o...

See all answers

What do you like most about Spring MVC?

The best feature of Spring MVC is its auto-configuration capabilities.

See all answers

What is your experience regarding pricing and costs for Spring MVC?

The solution is free.

See all answers

What needs improvement with Spring MVC?

In the future, 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.

See all answers

Comparisons

Spring Boot vs Apache Spark

Compared 27% of the time

SAP HANA vs Apache Spark

Compared 12% of the time

AWS Batch vs Apache Spark

Compared 11% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 7% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

More Apache Spark Competitors

Jakarta EE vs Spring MVC

Compared 56% of the time

Spring Boot vs Spring MVC

Compared 14% of the time

Oracle Application Development Framework vs Spring MVC

Compared 9% of the time

Open Liberty vs Spring MVC

Compared 7% of the time

Amazon Corretto vs Spring MVC

Compared 6% of the time

More Spring MVC Competitors

Product Reports

Buyer's Guide

Apache Spark

April 2025

Download Apache Spark product report

Buyer's Guide

Spring MVC

March 2025

Download Spring MVC product report

Also Known As

No data available

Spring by Pivotal, Spring, Spring Framework

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

Apache

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 MVC, View Technologies, CORS Support, and WebSocket Support.

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

VMware

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

Buyer's Guide

Apache Spark vs. Spring MVC

April 2025

Free Report: Apache Spark vs. Spring MVC

Find out what your peers are saying about Apache Spark vs. Spring MVC and other solutions. Updated: April 2025.

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