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

4,837 Views
1,741 Comparison Views

90% willing to recommend

Oracle Application Developm...

Read 9 Oracle Application Development Framework reviews

687 Views
680 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

"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 product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."

"The product's deployment phase is easy."

"I appreciate everything about the solution, not just one or two specific features. The solution is highly stable. I rate it a perfect ten. The solution is highly scalable. I rate it a perfect ten. The initial setup was straightforward. I recommend using the solution. Overall, I rate the solution a perfect ten."

"This solution provides a clear and convenient syntax for our analytical tasks."

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

"I feel the streaming is its best feature."

"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."

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."

"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 features of this solution are 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."

More Oracle Application Development Framework pros

Cons

"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."

"Its UI can be better. Maintaining the history server is a little cumbersome, and it should be improved. I had issues while looking at the historical tags, which sometimes created problems. You have to separately create a history server and run it. Such things can be made easier. Instead of separately installing the history server, it can be made a part of the whole setup so that whenever you set it up, it becomes available."

"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."

"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."

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

"The graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate."

"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."

"The initial setup was not easy."

More Apache Spark cons

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

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

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

"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."

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

"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."

More Oracle Application Development Framework cons

Pricing and Cost Advice

"The product is expensive, considering the setup."

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

"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."

"Apache Spark is an open-source tool."

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

"It is an open-source solution, it is free of charge."

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

"We are using the free version of the solution."

More Apache Spark pricing and cost advice

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

"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 have yearly licensing costs."

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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

11%

Manufacturing Company

10%

Government

10%

Non Profit

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 11% 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 62% of the time

Jakarta EE vs Oracle Application Development Framework

Compared 19% 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

July 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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