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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
7.7
Number of Reviews
66
Ranking in other categories
Hadoop (1st), Compute Service (4th)
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 April 2025, in the Java Frameworks category, the mindshare of Apache Spark is 5.5%, down from 7.5% compared to the previous year. The mindshare of Eclipse MicroProfile is 6.4%, down from 8.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks
 

Featured Reviews

Ilya Afanasyev - PeerSpot reviewer
Reliable, able to expand, and handle large amounts of data well
We use batch processing. It works well with our formats and file versions. There's a lot of functionality. In our pipeline each hour, we make a copy of data from MongoDB, of the changes from MongoDB to some specific file. Each time pipeline copied all of the data, it would do it each time without changes to all of the tables. Tables have a lot of data, and in the last MongoDB version, there is a possibility to read only changed data. This reduced the cost and configuration of the cluster, and we saved about $150,000. The solution is scalable. It's a stable product.
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 fault tolerant feature is provided."
"The product is useful for analytics."
"The solution is very stable."
"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."
"One of the key features is that Apache Spark is a distributed computing framework. You can help multiple slaves and distribute the workload between them."
"The scalability has been the most valuable aspect of the solution."
"The deployment of the product is easy."
"Apache Spark can do large volume interactive data analysis."
"Provides a lightweight runtime."
"We use the solution to create microservices."
"The solution is stable."
 

Cons

"We are building our own queries on Spark, and it can be improved in terms of query handling."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"At the initial stage, the product provides no container logs to check the activity."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"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."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"The tool needs to improve its messaging."
"Deployment of microservers in the Kubernetes environment is difficult."
"Its performance speed could be improved while working on the browser."
 

Pricing and Cost Advice

"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 expensive solution."
"We are using the free version of the solution."
"It is an open-source platform. We do not pay for its subscription."
"They provide an open-source license for the on-premise version."
"It is an open-source solution, it is free of charge."
"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."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
27%
Computer Software Company
13%
Manufacturing Company
8%
Comms Service Provider
6%
Financial Services Firm
21%
Computer Software Company
12%
Government
8%
Manufacturing Company
7%
 

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?
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 Spark solution could improve in scheduling tasks and managing dependencies. Spark alone cannot handle sequential tasks, requiring environments like Airflow scheduler or scripts. For instance, o...
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...
What needs improvement with Eclipse MicroProfile?
The solution's performance speed could be better while working on the browser. Also, they should include an option for online publishing. It will make sharing work easier. We can just publish work ...
 

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. Eclipse MicroProfile and other solutions. Updated: April 2025.
849,190 professionals have used our research since 2012.