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 #5 with an average rating of 9.0. Apache holds a 7.9% mindshare in JF, compared to VMware’s 3.4% 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

4,837 Views
1,741 Comparison Views

90% willing to recommend

Spring MVC

Read 16 Spring MVC reviews

927 Views
853 Comparison Views

89% willing to recommend

Apache Spark

Spring MVC

Comparison Buyer's Guide

Download the report

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: June 2025).

Buyer's Guide

Apache Spark vs. Spring MVC

June 2025

Download the complete report

Helped 861,524 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

7.4

Number of Reviews

Ranking in other categories

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

Spring MVC

Ranking in Java Frameworks

5th

Average Rating

8.4

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2025, in the Java Frameworks category, the mindshare of Apache Spark is 7.9%, down from 8.3% compared to the previous year. The mindshare of Spring MVC is 3.4%, up from 3.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Java Frameworks

Featured Reviews

Dunstan Matekenya

Data Scientist at a financial services firm with 10,001+ employees

Open-source solution for data processing with portability

Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly. While many choices now exist, Spark remains easy to use, particularly with Python. You can utilize familiar programming styles similar to Pandas in Python, including object-oriented programming. Another advantage is its portability. I can prototype and perform some initial tasks on my laptop using Spark without needing to be on Databricks or any cloud platform. I can transfer it to Databricks or other platforms, such as AWS. This flexibility allows me to improve processing even on my laptop. For instance, if I'm processing large amounts of data and find my laptop becoming slow, I can quickly switch to Spark. It handles small and large datasets efficiently, making it a versatile tool for various data processing needs.

Read full review

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

"The processing time is very much improved over the data warehouse solution that we were using."

"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."

"There's a lot of functionality."

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

"The fault tolerant feature is provided."

"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."

"We use Spark to process data from different data sources."

"I appreciate everything about the solution, not just one or two specific features. The solution is highly stable. I rate it a perfect ten. The solution is highly scalable. I rate it a perfect ten. The initial setup was straightforward. I recommend using the solution. Overall, I rate the solution a perfect ten."

More Apache Spark pros

"We appreciate that this product is really easy to integrate with third-party UI services."

"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."

"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."

"The most valuable feature is simplicity."

"Spring MVC is fast and reliable."

"The most valuable feature of Spring MVC is the configuration, such as WAF."

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

"Spring MVC's extensive documentation is the most valuable feature."

More Spring MVC pros

Cons

"I would like to see integration with data science platforms to optimize the processing capability for these tasks."

"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."

"The initial setup was not easy."

"The setup I worked on was really complex."

"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."

"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."

"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."

"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."

More Apache Spark cons

"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."

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

"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 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."

"We would like the deployment of this solution to be easier as, at present, it is quite complicated."

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

"It could provide faster performance."

"The initial setup could be more straightforward."

More Spring MVC cons

Pricing and Cost Advice

"They provide an open-source license for the on-premise version."

"I did not pay anything when using the tool on cloud services, but I had to pay on the compute side. The tool is not expensive compared with the benefits it offers. I rate the price as an eight out of ten."

"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."

"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."

"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."

"It is an open-source platform. We do not pay for its subscription."

"The product is expensive, considering the setup."

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

More Apache Spark pricing and cost advice

"It is an open-source solution."

"Spring MVC is open source and free."

"The solution is free."

"It is an affordable solution."

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

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

See which vendors are best for you

Use our free recommendation engine to learn which Java Frameworks solutions are best for your needs.

See recommendations

861,524 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

12%

Manufacturing Company

Comms Service Provider

Financial Services Firm

25%

Computer Software Company

20%

Comms Service Provider

Real Estate/Law Firm

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?

Apache Spark is open-source, so it doesn't incur any charges.

See all answers

What needs improvement with Apache Spark?

There is complexity when it comes to understanding the whole ecosystem, especially for beginners. I find it quite complex to understand how a Spark job is initiated, the roles of driver nodes, work...

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 25% of the time

AWS Batch vs Apache Spark

Compared 11% of the time

SAP HANA vs Apache Spark

Compared 10% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 6% of the time

More Apache Spark Competitors

Jakarta EE vs Spring MVC

Compared 45% of the time

IBM Open Liberty vs Spring MVC

Compared 13% of the time

Oracle Application Development Framework vs Spring MVC

Compared 11% of the time

Spring Boot vs Spring MVC

Compared 11% of the time

Amazon Corretto vs Spring MVC

Compared 9% of the time

More Spring MVC Competitors

Product Reports

Buyer's Guide

Apache Spark

July 2025

Download Apache Spark product report

Buyer's Guide

Spring MVC

June 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

June 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: June 2025.

DOWNLOAD NOW

861,524 professionals have used our research since 2012.

See our Apache Spark vs. Spring MVC report.

See our list of best Java Frameworks vendors.

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.