Try our new research platform with insights from 80,000+ expert users

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
7.3
Number of Reviews
67
Ranking in other categories
Hadoop (1st), Compute Service (4th)
Eclipse MicroProfile
Ranking in Java Frameworks
5th
Average Rating
8.4
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the Java Frameworks category, the mindshare of Apache Spark is 8.1%, up from 8.0% compared to the previous year. The mindshare of Eclipse MicroProfile is 7.1%, down from 7.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks
 

Featured Reviews

Omar Khaled - PeerSpot reviewer
Empowering data consolidation and fast decision-making with efficient big data processing
I can improve the organization's functions by taking less time to make decisions. To make the right decision, you need the right data, and a solution can provide this by hiring talent and employees who can consolidate data from different sources and organize it. Not all solutions can make this data fast enough to be used, except for solutions such as Apache Spark Structured Streaming. To make the right decision, you should have both accurate and fast data. Apache Spark itself is similar to the Python programming language. Python is a language with many libraries for mathematics and machine learning. Apache Spark is the solution, and within it, you have PySpark, which is the API for Apache Spark to write and run Python code. Within it, there are many APIs, including SQL APIs, allowing you to write SQL code within a Python function in Apache Spark. You can also use Apache Spark Structured Streaming and machine learning APIs.
Idris Oyibo Igagwu - PeerSpot reviewer
Scalable solution with an easy initial setup process
We use the solution for managing large programs, customer interactions, testing, and calculation purposes of our finance-based company The solution's most valuable feature is its ability to support dynamic developer profiles. We can easily create multiple accounts and rooms for different…

Quotes from Members

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

Pros

"The most valuable feature of Apache Spark is its flexibility."
"The processing time is very much improved over the data warehouse solution that we were using."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"I feel the streaming is its best feature."
"The data processing framework is good."
"It provides a scalable machine learning library."
"Apache Spark can do large volume interactive data analysis."
"The product's initial setup phase was easy."
"The solution is stable."
"Provides a lightweight runtime."
"We use the solution to create microservices."
 

Cons

"It's not easy to install."
"Spark could be improved by adding support for other open-source storage layers than Delta Lake."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"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 should support more programming languages."
"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."
"Deployment of microservers in the Kubernetes environment is difficult."
"Its performance speed could be improved while working on the browser."
"The tool needs to improve its messaging."
 

Pricing and Cost Advice

"Apache Spark is an open-source tool."
"We are using the free version of the solution."
"The solution is affordable and there are no additional licensing costs."
"It is an open-source solution, it is free of charge."
"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."
"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."
"It is an open-source platform. We do not pay for its subscription."
Information not available
report
Use our free recommendation engine to learn which Java Frameworks solutions are best for your needs.
865,384 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
10%
Manufacturing Company
7%
Comms Service Provider
7%
Financial Services Firm
24%
Manufacturing Company
9%
Computer Software Company
9%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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...
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: July 2025.
865,384 professionals have used our research since 2012.