Apache Spark vs Oracle Application Development Framework comparison

Apache and Oracle are both solutions in the Java Frameworks category. Apache is ranked #2 with an average rating of 8.8, while Oracle is ranked #8. Apache holds a 8.4% mindshare in JF, compared to Oracle’s 4.6% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 87% of Oracle users who would recommend it.

Apache Spark

Read 67 Apache Spark reviews

3,659 Views
1,281 Comparison Views

90% willing to recommend

Oracle Application Developm...

Read 9 Oracle Application Development Framework reviews

592 Views
586 Comparison Views

87% willing to recommend

Apache Spark

Oracle Application Developm...

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Executive Summary

We performed a comparison between Apache Spark and Oracle Application Development Framework based on real PeerSpot user reviews.

Find out in this report how the two Java Frameworks solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Apache Spark vs. Oracle Application Development Framework Report (Updated: September 2025).

Buyer's Guide

Apache Spark vs. Oracle Application Development Framework

September 2025

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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

Ranking in other categories

Hadoop (2nd), Compute Service (4th)

Oracle Application Developm...

Ranking in Java Frameworks

8th

Average Rating

7.8

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2025, in the Java Frameworks category, the mindshare of Apache Spark is 8.4%, up from 7.8% compared to the previous year. The mindshare of Oracle Application Development Framework is 4.6%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Java Frameworks Market Share Distribution
Product	Market Share (%)
Apache Spark	8.4%
Oracle Application Development Framework	4.6%
Other	87.0%

Java Frameworks

Featured Reviews

Omar Khaled

Data Engineer at a tech company with 10,001+ employees

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.

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Asad Ur Rehman

ERP Manager | Implementation Head at Tharsol

Eases the writing of code in Java with JavaBeans; easy to set up

My advice to anyone who intends to use ADF for the first time is that you must make sure that you have powerful enough hardware in order to run everything smoothly, especially when it comes to JDeveloper. If your hardware is adequate, you can get by without a problem in terms of speed, but be advised that it can use a lot of resources. However, even though ADF is a good product with great scalability that has really helped me out in hard times since 2014, I would ultimately recommend that new users look toward Oracle APEX instead of ADF. I would rate Oracle Application Development Framework a nine out of ten.

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Quotes from Members

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

Pros

"Spark is used for transformations from large volumes of data, and it is usefully distributed."

"Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly."

"The product's deployment phase is easy."

"Spark can handle small to huge data and is suitable for any size of company."

"I feel the streaming is its best feature."

"The most valuable feature of this solution is its capacity for processing large amounts of data."

"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."

"Apache Spark provides a very high-quality implementation of distributed data processing."

More Apache Spark pros

"The power of Oracle ADF is in the business components."

"The best part of Oracle ADF is being able to easily write code in Java with JavaBean files."

"The most valuable features of this solution are the business components."

"We can create objects that allow us to develop pages and applications very rapidly."

"The most valuable feature is the ease of integration with other Oracle products."

"It's database-centric, and it's seemingly easy to use the model–view–controller pattern that's built-in."

"The single sign-on features applied to Oracle Cloud is a valuable feature. All parts of this application are compatible with single sign-on, where you have a security feature that is very good in Oracle Cloud."

"There are several valuable features. First is the fast deployment. Also the ease of use."

More Oracle Application Development Framework pros

Cons

"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."

"One limitation is that not all machine learning libraries and models support it."

"In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, do the transformation in a subsecond, and all that."

"At the initial stage, the product provides no container logs to check the activity."

"They could improve the issues related to programming language for the platform."

"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."

"We are building our own queries on Spark, and it can be improved in terms of query handling."

"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."

More Apache Spark cons

"The UI is very slow and not up to market standard."

"The performance of this solution needs to be improved because it is very slow."

"Oracle ADF needs more components and the layout can be improved."

"The application needs to be more lightweight and the performance improved."

"I use JDeveloper along with ADF and, unfortunately, JDeveloper is a very slow tool. It takes a lot of time to accomplish things with it during both development and deployment. I hope that Oracle will improve JDeveloper to make it run faster."

"Oracle Application Development Framework is set to go out of support over the next three years but they should provide support for the solution for the longer term. Additionally, there needs to be more overall optimization and specifically in webpage rendering. The solution uses a lot of resources, and in order for them to move forward, they would have to create a smaller resource impact."

"You need to have Oracle ADF on-premises to build a big project. You need to have a dependable front-end application."

"The model layer could be improved for performance because once that part gets bloated, the performance is lacking. So, there is room for performance optimization."

More Oracle Application Development Framework cons

Pricing and Cost Advice

"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."

"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."

"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."

"The solution is affordable and there are no additional licensing costs."

"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 open-source. You have to pay only when you use any bundled product, such as Cloudera."

"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."

More Apache Spark pricing and cost advice

"The solution has an annual licensing cost and there are only standard fees. If you want Oracle support this is charged extra on top of the licensing fees."

"Oracle ADF is an expensive product. I don't know the actual figures, but our licensing costs for the year 2020, for example, were very high."

"We have yearly licensing costs."

"The cost of this solution is approximately $47,000 USD per site."

"We use a lot of Oracle products and in total, we pay about £5 million ($6.1 million USD) per year."

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

11%

Manufacturing Company

Comms Service Provider

Insurance Company

12%

Computer Software Company

10%

Manufacturing Company

10%

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	27
Midsize Enterprise	15
Large Enterprise	32

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	2
Large Enterprise	1

Questions from the Community

What do you like most about Apache Spark?

We use Spark to process data from different data sources.

See all answers

What is your experience regarding pricing and costs for Apache Spark?

Apache Spark is open-source, so it doesn't incur any charges.

See all answers

What needs improvement with Apache Spark?

Regarding Apache Spark, I have only used Apache Spark Structured Streaming, not the machine learning components. I am uncertain about specific improvements needed today. However, after five years, ...

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Compared 7% of the time

Apache NiFi vs Apache Spark

Compared 6% of the time

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Compared 51% of the time

Jakarta EE vs Oracle Application Development Framework

Compared 21% of the time

Spring MVC vs Oracle Application Development Framework

Compared 15% of the time

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Product Reports

Buyer's Guide

Apache Spark

November 2025

Download Apache Spark product report

Buyer's Guide

Java Frameworks

November 2025

Oracle Application Development Framework report

Download Oracle Application Development Framework product report

Also Known As

No data available

Oracle ADF

Overview

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

Apache

Oracle ADF is an end-to-end Java EE framework that simplifies application development by providing out-of-the-box infrastructure services and a visual and declarative development experience. Oracle ADF simplifies Java EE development by minimizing the need to write code that implements the applicationâs infrastructure allowing the developers to focus on the features of the actual application. Oracle ADF provides these infrastructure implementations as part of the framework. It also implements the Model-View-Controller design pattern and offers an integrated solution that covers all the layers of the architecture integrated with the Oracle SOA and WebCenter Portal frameworks.

Oracle

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

Financial Regulatory Authority (FRA) of Egypt, Red Samurai, ChB Jelly House

Buyer's Guide

Apache Spark vs. Oracle Application Development Framework

September 2025

Free Report: Apache Spark vs. Oracle Application Development Framework

Find out what your peers are saying about Apache Spark vs. Oracle Application Development Framework and other solutions. Updated: September 2025.

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