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Apache Spark vs Spring Boot comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 20, 2025

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
7.4
Number of Reviews
66
Ranking in other categories
Hadoop (1st), Compute Service (4th)
Spring Boot
Ranking in Java Frameworks
1st
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
38
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2025, in the Java Frameworks category, the mindshare of Apache Spark is 7.9%, down from 8.2% compared to the previous year. The mindshare of Spring Boot is 40.5%, down from 43.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks
 

Q&A Highlights

MT
Aug 28, 2023
 

Featured Reviews

Dunstan Matekenya - PeerSpot reviewer
Open-source solution for data processing with portability
Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly. While many choices now exist, Spark remains easy to use, particularly with Python. You can utilize familiar programming styles similar to Pandas in Python, including object-oriented programming. Another advantage is its portability. I can prototype and perform some initial tasks on my laptop using Spark without needing to be on Databricks or any cloud platform. I can transfer it to Databricks or other platforms, such as AWS. This flexibility allows me to improve processing even on my laptop. For instance, if I'm processing large amounts of data and find my laptop becoming slow, I can quickly switch to Spark. It handles small and large datasets efficiently, making it a versatile tool for various data processing needs.
Aniruddh Kurundkar - PeerSpot reviewer
A stable and scalable solution with good Load Balancer and Spring Cloud Gateway
We have specific algorithms for our Load Balancer or API gateway. So those things, if they could make it more precise, that would be beneficial. Sometimes when we are under pressure or any new person who looks into that stuff, we'll get confused or scared because of some difficulties in understanding Which algorithm needs to be used to implement a Load Balancer. When when we Yeah. Because when we say circuit breaker, we need to use it, and then the user gets a blank circuit breaker. This means we are saying the circuit breaker needs to be moved, and then that circuit breaker needs to be elaborated more. What type of algorithm should I do, and what exactly do I need to get done so that this circuit breaker can help me to resolve my issue? Because, you know, because if you go for the circuit breaker, it will ask to open the new tab, you know, since it will check. If the service is not responding, it will wait and go for another connection. So in similar words, if they can explain it a bit more, that will be helpful. Everyone could do their own Google stuff, and they will get it, but they need help understanding how this could help them to resolve the issue. It will be good if Spring Boot provides information about real-time use cases.

Quotes from Members

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

Pros

"Apache Spark provides a very high-quality implementation of distributed data processing."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"The product's deployment phase is easy."
"Apache Spark can do large volume interactive data analysis."
"Spark is used for transformations from large volumes of data, and it is usefully distributed."
"This solution provides a clear and convenient syntax for our analytical tasks."
"The most valuable feature of Apache Spark is its flexibility."
"The data processing framework is good."
"The Spring Cloud Gateway, Load Balancer are the valuable features. Apart from them, handling a sync call, then multiple service communication through field clients are also useful features."
"The solution's framework is stable."
"Spring Boot is much easier when it comes to the configuration, setup, installation, and deployment of your applications, compared to any kind of MVC framework. It has everything within a single framework."
"Spring Boot facilitates the use of Java which is open source. We use Github and other libraries that are available which assist in the building we need to do."
"This is a pretty light solution. It's not too heavy."
"I have found the starter solutions valuable, as well as integration with other products."
"The simplicity is excellent."
"It is a stable solution. Stability-wise, I rate the solution a nine out of ten...The initial setup was not complex and was a simple process."
 

Cons

"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"It should support more programming languages."
"From my perspective, the only thing that needs improvement is the interface, as it was not easily understandable."
"The migration of data between different versions could be improved."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"Its UI can be better. Maintaining the history server is a little cumbersome, and it should be improved. I had issues while looking at the historical tags, which sometimes created problems. You have to separately create a history server and run it. Such things can be made easier. Instead of separately installing the history server, it can be made a part of the whole setup so that whenever you set it up, it becomes available."
"Having to restart the application to reload properties."
"This solution could be improved if there were more libraries available. We would also like more mobile platform functionality using low levels of code."
"They should include tutorial videos for learning new features."
"They should integrate the solution with more AI and machine learning platforms."
"Building a new product in Spring Boot can take a long time since the solution uses reflection. This is one area the solution could be improved."
"We'd like to have fewer updates."
"The tool's documentation could be improved, especially by tying it back to frequently asked questions and issues users have. A feedback loop in which the documentation targets the most commonly asked user questions would make using the solution easier. Essentially, I want a more user-centered approach to documentation rather than a purely technical focus."
"If you want to create large microservices applications, you need to connect several applications and services to each other. It is very complicated, and Spring Boot does not have an integrated solution for it."
 

Pricing and Cost Advice

"They provide an open-source license for the on-premise version."
"It is an open-source platform. We do not pay for its subscription."
"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."
"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
"It is an open-source solution, it is free of charge."
"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."
"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."
"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."
"Spring Boot is an open-source solution."
"This solution is free unless you apply for support."
"The solution is free."
"It's open-source software, so it's free. It's a community license."
"The solution is an open-source tool."
"This is an open source solution."
"I am using a free version of Spring Boot."
"This is an open-source product."
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Top Industries

By visitors reading reviews
Financial Services Firm
27%
Computer Software Company
13%
Manufacturing Company
7%
Comms Service Provider
6%
Financial Services Firm
30%
Computer Software Company
12%
Manufacturing Company
7%
Government
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?
Apache Spark is open-source, so it doesn't incur any charges.
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...
What do you like most about Spring Boot?
1. Open Source2. Excellent Community Support -- Widely used across different projects -- so your search for answers would be easy and almost certain.3. Extendable Stack with a wide array of availab...
Which is better - Spring Boot or Eclipse MicroProfile?
Springboot is a Java-based solution that is very popular and easy to use. You can use it to build applications quickly and confidently. Springboot has a very large, helpful learning community, whic...
Which is better - Spring Boot or Jakarta EE?
Our organization ran comparison tests to determine whether the Spring Boot or Jakarta EE application creation software was the better fit for us. We decided to go with Spring Boot. Spring Boot offe...
 

Comparisons

 

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
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Find out what your peers are saying about Apache Spark vs. Spring Boot and other solutions. Updated: June 2025.
856,873 professionals have used our research since 2012.