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Apache Spark vs Eclipse MicroProfile comparison

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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
6th
Average Rating
8.4
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2026, in the Java Frameworks category, the mindshare of Apache Spark is 11.7%, up from 8.5% compared to the previous year. The mindshare of Eclipse MicroProfile is 7.6%, up from 7.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks Mindshare Distribution
ProductMindshare (%)
Apache Spark11.7%
Eclipse MicroProfile7.6%
Other80.7%
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 that Apache Spark can handle multiple tasks parallelly, and I also like the automation feature, while JavaScript helps with the parallel streaming of the library."
"The product's initial setup phase was easy."
"It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."
"Spark can handle small to huge data and is suitable for any size of company."
"There's a lot of functionality."
"The 2.3 version is quite stable, all of our customers use it, there are around 100,000+ users, and it runs 24/7."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"Apache Spark is a framework, which allows one organization to perform business and data analytics, at a very low cost, as compared to Ab-Initio or Informatica."
"Provides a lightweight runtime."
"We use the solution to create microservices."
"A great feature is the lightweight runtime."
"The solution is stable."
 

Cons

"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."
"The solution must improve its performance."
"It's not easy to install."
"The setup I worked on was really complex."
"The Spark solution could improve in scheduling tasks and managing dependencies."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"The solution’s integration with other platforms should be improved."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"The tool needs to improve its messaging."
"The most difficult part is deployment of the microservers in the Kubernetes environment and building the mechanisms for automated testing."
"Its performance speed could be improved while working on the browser."
 

Pricing and Cost Advice

"Spark is an open-source solution, so there are no licensing costs."
"Considering the product version used in my company, I feel that the tool is not costly since the product is available for 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."
"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
"We are using the free version of the solution."
"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
"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."
"They provide an open-source license for the on-premise version."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Outsourcing Company
10%
Comms Service Provider
9%
Construction Company
8%
Financial Services Firm
19%
University
14%
Insurance Company
13%
Comms Service Provider
7%
 

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: October 2026.
920,769 professionals have used our research since 2012.