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 9.5. Apache holds a 8.1% mindshare in JF, compared to VMware’s 3.3% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 88% of VMware users who would recommend it.

Apache Spark

Read 67 Apache Spark reviews

4,468 Views
1,608 Comparison Views

90% willing to recommend

Spring MVC

Read 15 Spring MVC reviews

841 Views
774 Comparison Views

88% 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: July 2025).

Buyer's Guide

Apache Spark vs. Spring MVC

July 2025

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Helped 865,985 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

7.3

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 August 2025, in the Java Frameworks category, the mindshare of Apache Spark is 8.1%, up from 8.0% compared to the previous year. The mindshare of Spring MVC is 3.3%, 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	8.1%
Spring MVC	3.3%
Other	88.6%

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

"Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly."

"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 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."

"The most valuable feature of Apache Spark is its ease of use."

"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."

"The solution has been very stable."

"I feel the streaming is its best feature."

"There's a lot of functionality."

More Apache Spark pros

"The solution can scale."

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

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

"Dependency Injection is one of the major features which makes our life easier using Spring. It is well documented and has active communities, which provide us enormous help."

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

"The most valuable feature is simplicity."

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

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

More Spring MVC pros

Cons

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

"From my perspective, the only thing that needs improvement is the interface, as it was not easily understandable."

"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."

"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."

"Apache Spark lacks geospatial data."

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

"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."

"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

"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."

"I have recently had problems with the changes that were made using Spring Security."

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

"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."

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

"It could provide faster performance."

"The initial setup could be more straightforward."

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

More Spring MVC cons

Pricing and Cost Advice

"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."

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

"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."

"Apache Spark is an expensive solution."

"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."

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

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

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."

"Spring MVC is open source and free."

"The solution is free."

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Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

11%

Manufacturing Company

Comms Service Provider

Financial Services Firm

24%

Computer Software Company

17%

Comms Service Provider

Government

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	4
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?

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 24% of the time

AWS Batch vs Apache Spark

Compared 11% of the time

SAP HANA vs Apache Spark

Compared 9% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

More Apache Spark Competitors

Jakarta EE vs Spring MVC

Compared 41% of the time

Oracle Application Development Framework vs Spring MVC

Compared 13% of the time

Spring Boot vs Spring MVC

Compared 13% of the time

IBM Open Liberty 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

August 2025

Download Apache Spark product report

Buyer's Guide

Spring MVC

August 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

July 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: July 2025.

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