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

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
7.7
Number of Reviews
66
Ranking in other categories
Hadoop (1st), Compute Service (5th)
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 2025, in the Java Frameworks category, the mindshare of Apache Spark is 5.6%, down from 7.4% compared to the previous year. The mindshare of Jakarta EE is 13.7%, down from 23.3% 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.
Erick  Karanja - PeerSpot reviewer
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

"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."
"The solution is scalable."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"Spark can handle small to huge data and is suitable for any size of company."
"Provides a lot of good documentation compared to other solutions."
"It is useful for handling large amounts of data. It is very useful for scientific purposes."
"The feature that allows a variation of work space based on the application being used."
"Jakarta EE's best features include REST services, configuration, and persistent facilities. It's also incredibly cloud friendly."
"Configuring, monitoring, and ensuring observability is a straightforward process."
 

Cons

"Apache Spark should add some resource management improvements to the algorithms."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"One limitation is that not all machine learning libraries and models support it."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"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."
"It requires overcoming a significant learning curve due to its robust and feature-rich nature."
"The solution must improve its performance."
"They could improve the issues related to programming language for the platform."
"All the customization and plugins can make the interface too slow and heavy in some situations."
"It would be great if we could have a UI-based approach or easily include the specific dependencies we need."
"Jakarta EE's configuration could be simpler, which would make it more useful as a developer experience."
 

Pricing and Cost Advice

"Licensing costs can vary. For instance, when purchasing a virtual machine, you're asked if you want to take advantage of the hybrid benefit or if you prefer the license costs to be included upfront by the cloud service provider, such as Azure. If you choose the hybrid benefit, it indicates you already possess a license for the operating system and wish to avoid additional charges for that specific VM in Azure. This approach allows for a reduction in licensing costs, charging only for the service and associated resources."
"The solution is affordable and there are no additional licensing costs."
"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."
"They provide an open-source license for the on-premise version."
"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."
"Apache Spark is an expensive solution."
"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 an open-source tool."
"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.
851,604 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
13%
Manufacturing Company
8%
Comms Service Provider
6%
Financial Services Firm
14%
Computer Software Company
14%
Comms Service Provider
8%
Government
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?
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 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...
What do you like most about Jakarta EE?
Configuring, monitoring, and ensuring observability is a straightforward process.
What needs improvement with Jakarta EE?
Enhancements in configurations can be achieved by benchmarking against Spring Boot technology. It would be great if we could have a UI-based approach or easily include the specific dependencies we ...
 

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 2025.
851,604 professionals have used our research since 2012.