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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
Number of Reviews
64
Ranking in other categories
Hadoop (1st), Compute Service (4th)
Spring MVC
Ranking in Java Frameworks
4th
Average Rating
8.4
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
Feb 20, 2024
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
Dec 20, 2023
A scalable tool with great auto-configuration capabilities
With Spring MVC, I have only developed things based on problems. Spring MVC follows monolithic architectures, and it also includes monorepo. Spring MVC takes care of the implementation of controllers along with areas like controller class and service class. Spring MVC allows me to work with REST…

Quotes from Members

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

Pros

"ETL and streaming capabilities."
"With Spark, we parallelize our operations, efficiently accessing both historical and real-time data."
"The most valuable feature of Apache Spark is its ease of use."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"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."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"The main feature that we find valuable is that it is very fast."
"Apache Spark can do large volume interactive data analysis."
"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."
"We have found Spring is easy to use and learn."
"Spring gives you the opportunity to develop architecture in the simplest way possible. It comes with everything you would want in terms of security. If you want to access the database, you have the ability to do that."
"We appreciate that this product is really easy to integrate with third-party UI services."
"Spring has a speedy development process with a lightweight framework."
"Spring MVC is fast and reliable."
"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."
 

Cons

"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"Apache Spark should add some resource management improvements to the algorithms."
"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."
"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."
"When using Spark, users may need to write their own parallelization logic, which requires additional effort and expertise."
"The main concern is the overhead of Java when distributed processing is not necessary."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"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."
"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."
"The solution could be simplified quite a bit. It's unnecessarily complicated in some areas."
"It could provide faster performance."
"It can be difficult for a basic user to understand the concepts in this solution, such as inversion of control."
"Spring IDE​ needs some work and improvement. We have faced many issues when adding third-party Eclipse plugins."
"I saw some error messages coming up when they were getting problems actually viewing all the reports."
 

Pricing and Cost Advice

"Apache Spark is an open-source tool."
"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."
"We are using the free version of the solution."
"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 not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
"The product is expensive, considering the setup."
"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."
"Spring MVC is open source and free."
"It is an affordable solution."
"The solution is free."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
13%
Manufacturing Company
8%
Educational Organization
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
 

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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.
814,649 professionals have used our research since 2012.