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."Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"It is useful for handling large amounts of data. It is very useful for scientific purposes."
"The most valuable feature of Apache Spark is its memory processing because it processes data over RAM rather than disk, which is much more efficient and fast."
"It is highly scalable, allowing you to efficiently work with extensive datasets that might be problematic to handle using traditional tools that are memory-constrained."
"The product’s most valuable features are lazy evaluation and workload distribution."
"The fault tolerant feature is provided."
"Provides a lot of good documentation compared to other solutions."
"The product is useful for analytics."
"The most valuable feature of the Oracle Application Development Framework is the rapid development and the security it provides."
"The best part of Oracle ADF is being able to easily write code in Java with JavaBean files."
"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 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 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 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."
"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."
"Apache Spark should add some resource management improvements to the algorithms."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"The solution needs to optimize shuffling between workers."
"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."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"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."
"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."
"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 application needs to be more lightweight and the performance improved."
"Lacks tailoring to geographic regional differences and consistent integration with third parties."
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Apache Spark is ranked 2nd in Java Frameworks with 60 reviews while Oracle Application Development Framework is ranked 8th in Java Frameworks with 9 reviews. Apache Spark is rated 8.4, while Oracle Application Development Framework is rated 7.8. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of Oracle Application Development Framework writes "Eases the writing of code in Java with JavaBeans; easy to set up". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas Oracle Application Development Framework is most compared with Spring Boot, Jakarta EE and Spring MVC. See our Apache Spark vs. Oracle Application Development Framework report.
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