No more typing reviews! Try our Samantha, our new voice AI agent.

Apache Spark vs Jakarta EE 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)
Jakarta EE
Ranking in Java Frameworks
3rd
Average Rating
7.4
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2026, in the Java Frameworks category, the mindshare of Apache Spark is 11.2%, up from 7.4% compared to the previous year. The mindshare of Jakarta EE is 17.0%, down from 17.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Java Frameworks Mindshare Distribution
ProductMindshare (%)
Apache Spark11.2%
Jakarta EE17.0%
Other71.8%
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.
Erick  Karanja - PeerSpot reviewer
Technical Lead at Cellulant Kenya
A robust enterprise Java capabilities with complex configuration involved, making it a powerful choice for scalable applications while requiring a learning curve
When running applications in the cloud, scalability is highly dependent on how you configure it. Factors such as the number of instances you want to scale, and the threshold for scaling based on the quantity of messages or the amount of data, are all customizable based on your application's needs.

Quotes from Members

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

Pros

"We are able to solve problems, e.g., reporting on big data, that we were not able to tackle in the past."
"We are using Apache Spark, for large volume interactive data analysis."
"Having everything in the same framework has helped us out a lot."
"Spark can handle small to huge data and is suitable for any size of company."
"After using Spark, we were able to accomplish this task within hours."
"As it uses in-memory data processing, Spark is very fast."
"We have built a product called NetBot where we take any form of data, such as large email data, images, videos, or transactional data, and transform unstructured textual and video data into structured transactional data to create an enterprise-wide smart data grid that is then used by downstream analytics tools."
"The most valuable feature of this solution is its capacity for processing large amounts of data."
"The feature that allows a variation of work space based on the application being used."
"Configuring, monitoring, and ensuring observability is a straightforward process."
"Jakarta EE's best features include REST services, configuration, and persistent facilities. It's also incredibly cloud friendly."
"Eclipse is now on a good track and they have a very good interface."
 

Cons

"Its UI can be better. Maintaining the history server is a little cumbersome, and it should be improved."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"There is complexity when it comes to understanding the whole ecosystem, especially for beginners."
"The setup I worked on was really complex."
"I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it."
"The solution must improve its performance."
"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."
"All the customization and all the plugins we can install make the interface too slow and heavy in some situations."
"Jakarta EE's configuration could be simpler, which would make it more useful as a developer experience."
"It would be great if we could have a UI-based approach or easily include the specific dependencies we need."
"All the customization and plugins can make the interface too slow and heavy in some situations."
 

Pricing and Cost Advice

"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
"It is an open-source platform. We do not pay for its subscription."
"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."
"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."
"The solution is affordable and there are no additional licensing costs."
"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."
"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
"I would rate Jakarta EE's pricing seven out of ten."
report
Use our free recommendation engine to learn which Java Frameworks solutions are best for your needs.
893,221 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
23%
Comms Service Provider
7%
Manufacturing Company
7%
Computer Software Company
6%
Financial Services Firm
14%
Manufacturing Company
12%
Computer Software Company
10%
Comms Service Provider
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise16
Large Enterprise32
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 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
Information Not Available
Find out what your peers are saying about Apache Spark vs. Jakarta EE and other solutions. Updated: April 2026.
893,221 professionals have used our research since 2012.