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 #10. Apache holds a 5.6% mindshare in JF, compared to Oracle’s 2.6% 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

2,037 Views
1,544 Comparison Views

90% willing to recommend

Oracle Application Developm...

Read 9 Oracle Application Development Framework reviews

755 Views
480 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: April 2025).

Buyer's Guide

Apache Spark vs. Oracle Application Development Framework

April 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

7.7

Number of Reviews

Ranking in other categories

Hadoop (1st), Compute Service (5th)

Oracle Application Developm...

Ranking in Java Frameworks

10th

Average Rating

7.8

Reviews Sentiment

6.0

Number of Reviews

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 Oracle Application Development Framework is 2.6%, up from 2.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Java Frameworks

Featured Reviews

Ilya Afanasyev

Senior Software Development Engineer at Yahoo!

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.

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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

"It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."

"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more."

"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."

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

"The most significant advantage of Spark 3.0 is its support for DataFrame UDF Pandas UDF features."

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

"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."

"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."

More Apache Spark pros

"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 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 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."

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

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

More Oracle Application Development Framework pros

Cons

"The solution needs to optimize shuffling between workers."

"The solution must improve its performance."

"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."

"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."

"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."

"It requires overcoming a significant learning curve due to its robust and feature-rich nature."

"Apache Spark provides very good performance The tuning phase is still tricky."

"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."

More Apache Spark cons

"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."

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

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

"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."

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

"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."

More Oracle Application Development Framework cons

Pricing and Cost Advice

"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."

"The product is expensive, considering the setup."

"It is an open-source platform. We do not pay for its subscription."

"Apache Spark is an open-source tool."

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

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

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

More Apache Spark pricing and cost advice

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

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

"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 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."

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Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

13%

Manufacturing Company

Comms Service Provider

Computer Software Company

13%

Manufacturing Company

10%

Retailer

Government

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 27% of the time

AWS Batch vs Apache Spark

Compared 12% of the time

SAP HANA vs Apache Spark

Compared 11% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 7% of the time

More Apache Spark Competitors

Spring Boot vs Oracle Application Development Framework

Compared 69% 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

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Product Reports

Buyer's Guide

Apache Spark

May 2025

Download Apache Spark product report

Buyer's Guide

Java Frameworks

May 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

April 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: April 2025.

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