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Apache Spark vs Eclipse MicroProfile 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
6.9
Number of Reviews
69
Ranking in other categories
Hadoop (1st), Compute Service (6th)
Eclipse MicroProfile
Ranking in Java Frameworks
7th
Average Rating
8.4
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Java Frameworks category, the mindshare of Apache Spark is 11.8%, up from 8.1% compared to the previous year. The mindshare of Eclipse MicroProfile is 7.4%, up from 7.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks Mindshare Distribution
ProductMindshare (%)
Apache Spark11.8%
Eclipse MicroProfile7.4%
Other80.8%
Java Frameworks
 

Featured Reviews

Devindra Weerasooriya - PeerSpot reviewer
Data Architect at Devtech
Provides a consistent framework for building data integration and access solutions with reliable performance
The in-memory computation feature is certainly helpful for my processing tasks. It is helpful because while using structures that could be held in memory rather than stored during the period of computation, I go for the in-memory option, though there are limitations related to holding it in memory that need to be addressed, but I have a preference for in-memory computation. The solution is beneficial in that it provides a base-level long-held understanding of the framework that is not variant day by day, which is very helpful in my prototyping activity as an architect trying to assess Apache Spark, Great Expectations, and Vault-based solutions versus those proposed by clients like TIBCO or Informatica.
FABIO LUIS VELLOSO DA SILVA - PeerSpot reviewer
Partner at SouJava
A scalable and easy to setup solution
We use the solution to create microservices.  The tool needs to improve its messaging.  I don't have much more data or experience with stability.  The solution is scalable.  The tool's setup is easy.  I would rate the product a nine out of ten. It is very important to know Java, and issues…

Quotes from Members

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

Pros

"I like Apache Spark's flexibility the most. Before, we had one server that would choke up. With the solution, we can easily add more nodes when needed. The machine learning models are also really helpful. We use them to predict energy theft and find infrastructure problems."
"Faster time to parse and compute data makes web-based queries for plotting data easier."
"We have 1000x improvement in performance over other techniques."
"We are able to solve problems, e.g., reporting on big data, that we were not able to tackle in the past."
"The deployment of the product is easy."
"ETL and streaming capabilities."
"It is a very fast solution."
"Powerful language."
"Provides a lightweight runtime."
"The solution is stable."
"We use the solution to create microservices."
"A great feature is the lightweight runtime."
 

Cons

"I ran into Spark application performance issues."
"The basic improvement would be to have integration with these solutions."
"Better data lineage support."
"It needs to be simpler to use the machine learning algorithms supported by Octave (example polynomial regressions, polynomial interpolation)."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"It's not easy to install."
"At the initial stage, the product provides no container logs to check the activity."
"The tool needs to improve its messaging."
"Its performance speed could be improved while working on the browser."
"The most difficult part is deployment of the microservers in the Kubernetes environment and building the mechanisms for automated testing."
 

Pricing and Cost Advice

"Apache Spark is an open-source tool."
"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 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 open-source solution, and there is no cost involved in deploying the solution on-premises."
"They provide an open-source license for the on-premise version."
"Spark is an open-source solution, so there are no licensing costs."
"Apache Spark is an expensive solution."
"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Construction Company
9%
Manufacturing Company
8%
Comms Service Provider
7%
Financial Services Firm
20%
University
13%
Insurance Company
11%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise16
Large Enterprise33
No data available
 

Questions from the Community

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?
I find that there really lacks the technical depth to do any recommendations for future updates of Apache Spark. I used it for two years for our prototype work and testing things, but because I had...
What is your primary use case for Apache Spark?
I attempted to use Apache Spark in one of our customer projects, but after the initial test, our customer moved to another technology and another database system. I do not have any final remarks on...
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...
 

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
Information Not Available
Find out what your peers are saying about Apache Spark vs. Eclipse MicroProfile and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.