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 8.6, while Oracle is ranked #9. Apache holds a 7.9% mindshare in JF, compared to Oracle’s 3.6% 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 66 Apache Spark reviews

1,741 Views
1,288 Comparison Views

90% willing to recommend

Oracle Application Developm...

Read 9 Oracle Application Development Framework reviews

680 Views
389 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: June 2025).

Buyer's Guide

Apache Spark vs. Oracle Application Development Framework

June 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

7.4

Number of Reviews

Ranking in other categories

Hadoop (1st), Compute Service (4th)

Oracle Application Developm...

Ranking in Java Frameworks

9th

Average Rating

7.8

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2025, in the Java Frameworks category, the mindshare of Apache Spark is 7.9%, down from 8.3% compared to the previous year. The mindshare of Oracle Application Development Framework is 3.6%, up from 2.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Java Frameworks

Featured Reviews

Dunstan Matekenya

Data Scientist at a financial services firm with 10,001+ employees

Open-source solution for data processing with portability

Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly. While many choices now exist, Spark remains easy to use, particularly with Python. You can utilize familiar programming styles similar to Pandas in Python, including object-oriented programming. Another advantage is its portability. I can prototype and perform some initial tasks on my laptop using Spark without needing to be on Databricks or any cloud platform. I can transfer it to Databricks or other platforms, such as AWS. This flexibility allows me to improve processing even on my laptop. For instance, if I'm processing large amounts of data and find my laptop becoming slow, I can quickly switch to Spark. It handles small and large datasets efficiently, making it a versatile tool for various data processing needs.

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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

"The product’s most valuable features are lazy evaluation and workload distribution."

"The product's deployment phase is easy."

"AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI."

"Apache Spark can do large volume interactive data analysis."

"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."

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

"Features include machine learning, real time streaming, and data processing."

"The data processing framework is good."

More Apache Spark pros

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

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

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

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

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

"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."

"The most valuable feature of the Oracle Application Development Framework is the rapid development and the security it provides."

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

More Oracle Application Development Framework pros

Cons

"Apache Spark should add some resource management improvements to the algorithms."

"The setup I worked on was really complex."

"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."

"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."

"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."

"The solution must improve its performance."

"Spark could be improved by adding support for other open-source storage layers than Delta Lake."

"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."

More Apache Spark cons

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

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

"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."

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

"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."

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

"Lacks tailoring to geographic regional differences and consistent integration with third parties."

"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."

More Oracle Application Development Framework cons

Pricing and Cost Advice

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

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

"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."

"They provide an open-source license for the on-premise version."

"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."

"Spark is an open-source solution, so there are no licensing costs."

"Apache Spark is an open-source tool."

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

More Apache Spark pricing and cost advice

"We have yearly licensing costs."

"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."

"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."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

12%

Manufacturing Company

Comms Service Provider

Computer Software Company

10%

Manufacturing Company

Government

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

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...

See all answers

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Comparisons

Spring Boot vs Apache Spark

Compared 25% of the time

AWS Batch vs Apache Spark

Compared 12% of the time

SAP HANA vs Apache Spark

Compared 10% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 6% of the time

More Apache Spark Competitors

Spring Boot vs Oracle Application Development Framework

Compared 61% of the time

Jakarta EE vs Oracle Application Development Framework

Compared 20% of the time

Spring MVC vs Oracle Application Development Framework

Compared 11% of the time

More Oracle Application Development Framework Competitors

Product Reports

Buyer's Guide

Apache Spark

June 2025

Download Apache Spark product report

Buyer's Guide

Java Frameworks

June 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

June 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: June 2025.

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