Apache Spark vs Spring MVC comparison

Apache and Broadcom are both solutions in the Java Frameworks category. Apache is ranked #2 with an average rating of 8.8, while Broadcom is ranked #4 with an average rating of 9.5. Apache holds a 8.4% mindshare in JF, compared to Broadcom’s 3.8% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

Apache Spark

Read 67 Apache Spark reviews

3,754 Views
1,351 Comparison Views

90% willing to recommend

Spring MVC

Read 15 Spring MVC reviews

815 Views
750 Comparison Views

88% 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: September 2025).

Buyer's Guide

Apache Spark vs. Spring MVC

September 2025

Download the complete report

Helped 871,408 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

6.9

Number of Reviews

Ranking in other categories

Hadoop (2nd), 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 October 2025, in the Java Frameworks category, the mindshare of Apache Spark is 8.4%, up from 7.8% compared to the previous year. The mindshare of Spring MVC is 3.8%, up from 3.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Java Frameworks Market Share Distribution
Product	Market Share (%)
Apache Spark	8.4%
Spring MVC	3.8%
Other	87.8%

Java Frameworks

Featured Reviews

Omar Khaled

Data Engineer at a tech company with 10,001+ employees

Empowering data consolidation and fast decision-making with efficient big data processing

I can improve the organization's functions by taking less time to make decisions. To make the right decision, you need the right data, and a solution can provide this by hiring talent and employees who can consolidate data from different sources and organize it. Not all solutions can make this data fast enough to be used, except for solutions such as Apache Spark Structured Streaming. To make the right decision, you should have both accurate and fast data. Apache Spark itself is similar to the Python programming language. Python is a language with many libraries for mathematics and machine learning. Apache Spark is the solution, and within it, you have PySpark, which is the API for Apache Spark to write and run Python code. Within it, there are many APIs, including SQL APIs, allowing you to write SQL code within a Python function in Apache Spark. You can also use Apache Spark Structured Streaming and machine learning APIs.

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

"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."

"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."

"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."

"I like Apache Spark's flexibility the most. Before, we had one server that would choke up. With the solution, we can easily add more nodes when needed. The machine learning models are also really helpful. We use them to predict energy theft and find infrastructure problems."

"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."

"The solution is very stable."

"There's a lot of functionality."

"With Spark, we parallelize our operations, efficiently accessing both historical and real-time data."

More Apache Spark pros

"It provides the best documentation for technical support."

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

"Spring MVC is fast and reliable."

"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 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 has a speedy development process with a lightweight framework."

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

"The solution can scale."

More Spring MVC pros

Cons

"It requires overcoming a significant learning curve due to its robust and feature-rich nature."

"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."

"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."

"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."

"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."

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

"For improvement, I think the tool could make things easier for people who aren't very technical. There's a significant learning curve, and I've seen organizations give up because of it. Making it quicker or easier for non-technical people would be beneficial."

More Apache Spark cons

"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 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."

"The initial setup could be more straightforward."

"It could provide faster performance."

"Spring MVC could improve the integration with DevOps and other applications."

"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 not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."

"It is an open-source solution, it is free of charge."

"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 solution, and there is no cost involved in deploying the solution on-premises."

"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 product is expensive, considering the setup."

"Apache Spark is an open-source tool."

"The solution is affordable and there are no additional licensing costs."

More Apache Spark pricing and cost advice

"The solution is free."

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

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

"It is an open-source solution."

"Spring MVC is open source and free."

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

871,408 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

11%

Comms Service Provider

Manufacturing Company

Financial Services Firm

23%

Computer Software Company

17%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	27
Midsize Enterprise	15
Large Enterprise	32

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	2
Large Enterprise	11

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?

Regarding Apache Spark, I have only used Apache Spark Structured Streaming, not the machine learning components. I am uncertain about specific improvements needed today. However, after five years, ...

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 23% of the time

AWS Batch vs Apache Spark

Compared 10% of the time

SAP HANA vs Apache Spark

Compared 9% of the time

AWS Lambda vs Apache Spark

Compared 7% of the time

Amazon Corretto vs Apache Spark

Compared 2% of the time

More Apache Spark Competitors

Jakarta EE vs Spring MVC

Compared 37% of the time

Oracle Application Development Framework vs Spring MVC

Compared 14% of the time

IBM Open Liberty vs Spring MVC

Compared 13% of the time

Spring Boot vs Spring MVC

Compared 12% of the time

Amazon Corretto vs Spring MVC

Compared 11% of the time

More Spring MVC Competitors

Product Reports

Buyer's Guide

Apache Spark

October 2025

Download Apache Spark product report

Buyer's Guide

Spring MVC

September 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.

Broadcom

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

September 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: September 2025.

DOWNLOAD NOW

871,408 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.