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 3.5% 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

1,939 Views
1,439 Comparison Views

90% willing to recommend

Oracle Application Developm...

Read 9 Oracle Application Development Framework reviews

718 Views
421 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 June 2025, in the Java Frameworks category, the mindshare of Apache Spark is 7.9%, down from 8.2% compared to the previous year. The mindshare of Oracle Application Development Framework is 3.5%, 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

"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 processing time is very much improved over the data warehouse solution that we were using."

"It is useful for handling large amounts of data. It is very useful for scientific purposes."

"We use it for ETL purposes as well as for implementing the full transformation pipelines."

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

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

"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."

"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."

More Apache Spark pros

"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."

"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."

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

"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."

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

More Oracle Application Development Framework pros

Cons

"Dynamic DataFrame options are not yet available."

"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."

"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."

"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."

"The setup I worked on was really complex."

"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."

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

"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."

More Apache Spark cons

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

"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."

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

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

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."

"The product is expensive, considering the setup."

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

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

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

"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."

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

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

More Apache Spark pricing and cost advice

"We have yearly licensing costs."

"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."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

13%

Manufacturing Company

Comms Service Provider

Computer Software Company

11%

Retailer

Government

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.

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

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

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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...

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Comparisons

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Compared 10% 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

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Compared 63% 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

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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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