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Apache Spark vs Spring MVC comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Apache Spark
Ranking in Java Frameworks
2nd
Average Rating
8.4
Reviews Sentiment
7.7
Number of Reviews
64
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 November 2024, in the Java Frameworks category, the mindshare of Apache Spark is 6.7%, down from 7.6% compared to the previous year. The mindshare of Spring MVC is 3.0%, up from 2.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks
 

Featured Reviews

SurjitChoudhury - PeerSpot reviewer
Offers batch processing of data and in-memory processing in Spark greatly enhances performance
Spark supports real-time data processing through Spark Streaming. It allows for batch processing of data. If you have immediate data, like chat information, that needs to be processed in real-time, Spark Streaming is used. For data that can be evaluated later, batch processing with Apache Spark is suitable. Mostly, batch processing is utilized in our organization, but for streaming data processing, tools like Kafka are often integrated. In-memory processing in Spark greatly enhances performance, making it a hundred times faster than the previous MapReduce methods. This improvement is achieved through optimization techniques like caching, broadcasting, and partitioning, which help in optimizing queries for faster processing.
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

"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"Provides a lot of good documentation compared to other solutions."
"There's a lot of functionality."
"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."
"Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly."
"The solution has been very stable."
"The solution is open-source and free to use."
"Spring MVC's extensive documentation is the most valuable feature."
"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."
"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 solution can scale."
"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."
 

Cons

"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."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"The setup I worked on was really complex."
"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."
"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."
"The initial setup was not easy."
"The documentation for Spring MVC could improve."
"I have recently had problems with the changes that were made using Spring Security."
"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."
"Spring MVC could improve the integration with DevOps and other applications."
"The solution could be simplified quite a bit. It's unnecessarily complicated in some areas."
"Spring IDE​ needs some work and improvement. We have faced many issues when adding third-party Eclipse plugins."
"The initial setup could be more straightforward."
 

Pricing and Cost Advice

"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."
"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."
"Apache Spark is an open-source tool."
"They provide an open-source license for the on-premise version."
"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."
"It is an open-source solution, it is free of charge."
"Spark is an open-source solution, so there are no licensing costs."
"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."
"Spring MVC is open source and free."
"We are using the open-source version of the solution."
"It is an open-source solution."
"It is an affordable 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
27%
Computer Software Company
13%
Manufacturing Company
8%
University
5%
Financial Services Firm
23%
Computer Software Company
19%
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 main concern is the overhead of Java when distributed processing is not necessary. In such cases, operations can often be done on one node, making Spark's distributed mode unnecessary. Conseque...
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
 

Learn More

 

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: October 2024.
816,406 professionals have used our research since 2012.