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Apache Spark vs Spring MVC comparison

 

Comparison Buyer's Guide

Executive Summary

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
65
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
16
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 - PeerSpot reviewer
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.
Arkabrata  Ghosh - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"The solution has been very stable."
"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."
"It provides a scalable machine learning library."
"Features include machine learning, real time streaming, and data processing."
"With Spark, we parallelize our operations, efficiently accessing both historical and real-time data."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"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."
"The best feature of Spring MVC is its auto-configuration capabilities."
"The solution is open-source and free to use."
"The most valuable feature of Spring MVC is the configuration, such as WAF."
"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."
"We have found Spring is easy to use and learn."
"We appreciate that this product is really easy to integrate with third-party UI services."
"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."
"The most valuable feature is simplicity."
 

Cons

"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"Spark could be improved by adding support for other open-source storage layers than Delta Lake."
"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."
"Dynamic DataFrame options are not yet available."
"It should support more programming languages."
"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."
"Apache Spark should add some resource management improvements to the algorithms."
"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 documentation for Spring MVC could improve."
"Spring MVC could improve the integration with DevOps and other applications."
"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."
"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."
"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."
"Spring IDE​ needs some work and improvement. We have faced many issues when adding third-party Eclipse plugins."
 

Pricing and Cost Advice

"They provide an open-source license for the on-premise version."
"The product is expensive, considering the setup."
"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."
"We are using the free version of the solution."
"It is an open-source platform. We do not pay for its subscription."
"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."
"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."
"Spring MVC is open source and free."
"It is an open-source solution."
"It is an affordable solution."
"We are using the open-source version of the solution."
"The solution is free."
"This is an open-source solution, so there are no license costs involved with using it."
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Top Industries

By visitors reading reviews
Financial Services Firm
28%
Computer Software Company
13%
Manufacturing Company
8%
Comms Service Provider
5%
Financial Services Firm
24%
Computer Software Company
21%
Government
8%
Comms Service Provider
6%
 

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.
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...
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...
What do you like most about Spring MVC?
The best feature of Spring MVC is its auto-configuration capabilities.
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.
 

Comparisons

 

Also Known As

No data available
Spring by Pivotal, Spring, Spring Framework
 

Overview

 

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
Find out what your peers are saying about Apache Spark vs. Spring MVC and other solutions. Updated: March 2025.
845,406 professionals have used our research since 2012.