Oracle Advanced Analytics vs Weka comparison

Oracle Advanced Analytics

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Executive SummaryUpdated on Jun 3, 2026

Oracle Advanced Analytics and Weka compete in the data analytics sector. Oracle Advanced Analytics seems to have an edge in environments requiring robust integration with existing ecosystems, while Weka is more flexible for exploratory machine learning tasks.

Features: Oracle Advanced Analytics boasts deep integration with enterprise systems, advanced statistical functions, and data mining capabilities. Weka offers a wide range of machine learning algorithms, a user-friendly interface, and the ability to process large data sets without programming skills.

Room for Improvement: Oracle Advanced Analytics could enhance its transparency in pricing and streamline user experience for non-Oracle systems. Weka could improve its data visualization tools and expand its support for enterprise-level deployment. Additionally, enhancing its integration with external databases might be beneficial.

Ease of Deployment and Customer Service: Oracle Advanced Analytics benefits from seamless integration within Oracle environments and strong support services, facilitating a smoother deployment for existing Oracle customers. Weka offers a straightforward installation process with vibrant community support, making it ideal for academic and small-scale enterprises.

Pricing and ROI: Oracle Advanced Analytics often involves higher initial costs, which can be offset by strong ROI through integration in Oracle ecosystems. Weka is more cost-effective initially due to its open-source model, providing significant ROI with lower entry prices and high flexibility in machine learning applications.

To learn more, read our detailed Oracle Advanced Analytics vs. Weka Report (Updated: September 2026).

Oracle Advanced Analytics vs. Weka

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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

Oracle Advanced Analytics

Ranking in Data Mining

6th

Average Rating

8.0

Reviews Sentiment

4.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Weka

Ranking in Data Mining

4th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (1st)

Mindshare comparison

As of October 2026, in the Data Mining category, the mindshare of Oracle Advanced Analytics is 4.9%, up from 3.9% compared to the previous year. The mindshare of Weka is 7.1%, down from 12.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Mindshare Distribution
Product	Mindshare (%)
Weka	7.1%
Oracle Advanced Analytics	4.9%
Other	88.0%

Data Mining

Featured Reviews

Prabhat_Ranjan

Technical Manager at LTM

Analytics features have improved our reporting workflows and support data‑driven decisions

The feature is called Oracle R Enterprise, and I have not worked with it. I have not used Oracle Enterprise. I am hearing about it for the first time. We have not used machine learning. We do not work with it for creating any data models from machine learning. My overall rating for this product is 8.

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Joseph Kaiser

Staff Infrastructure Engineer at a manufacturing company with 201-500 employees

High-speed shared storage has accelerated AI research workflows and supports massive job queues

The best features Weka offers are high speed, exceptional performance, and reliability. It is probably the best file system I have ever used. These features have helped my workflows and users by enabling us to train and perform inferencing of AI workflows of proteins against target diseases, which allows us to run jobs in approximately half the time that we would with slower storage. Weka is always available, incredibly reliable, and backed up, so we could not do this work without it. Additionally, Weka is incredibly easy to use because there is a web UI that allows us to create and resize file systems at will, making different directory structures available to different users at any given time, and the speed is exceptional. Weka has positively impacted my organization because we previously had NFS, which would take down the cluster when under high load. Now we have no concerns about highly loaded multiple thousands of jobs running simultaneously against this file system. The system handles it without any issues. To share more about the scale, we have anywhere between 1,000 to 10,000 jobs in the queue at any given time, and the system handles it without any problems. Our volumes are approximately half a petabyte on one system and about a third of a petabyte on another system for various storage uses, and it enables all our work to go efficiently.

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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

"Oracle Advanced Analytics effectively prevents threats and helps maintain a secure network environment."

"Oracle Data Mining provides a powerful functionality as it enables users to discover new insights hidden in data."

"We have used Oracle Data Miner, which has a drag-and-drop interface that creates the workflow and is easy to use to build workflow-based modeling."

"Oracle is number one in the world for security, safety, and privacy."

"One of the valuable features is the ability to pull together multiple sources of information and the tools are easy to use which is the main factor."

"Ability to pull together multiple sources of information."

"When it comes to data mining, I am acquainted with most or all of the Oracle tools and have had a positive experience with them."

"When needed, we will work closely with Oracle support and implement their workaround in our application."

More Oracle Advanced Analytics pros

"I like the machine algorithm for clustering systems. Weka has larger capabilities. There are multiple algorithms that can be used for clustering. It depends upon the user requirements. For clustering, I've used DBSCAN, whereas for supervised learning, I've used AVM and RFT."

"Weka is a very easy to use Data Mining solution, great for learning and for doing small experiments before exploring the data deeper, with a large number and diversity of algorithms that make it an excellent solution for rapid testing."

"Working with complicated algorithms in huge datasets is really easy in Weka."

"Using Weka has positively impacted my studies and projects because it has saved my time firstly."

"There are many options where you can fill all of the data pre-processing options that you can implement when you're importing the data. You can also normalize the data and standardize it in an easier way."

"I think Weka is definitely a good investment, that is why we still use it."

"But Weka helped me with this analysis in an easy way."

"Weka is very easy to use, is very complete, and provides many benefits to the end user."

More Weka pros

Cons

"Since a separate Oracle database is needed, the data loading and cleansing the raw data can be a time consuming process."

"Problems in handling huge data sets."

"Could use some refinement getting things that are not standard cloud applications, but more customized."

"Basic capabilities, less professional than would be expected from a company dealing with databases as a core business."

"The performance, scalability and queries should be addressed, as well as the data distribution of certain data techniques."

"From my perspective, there is sometimes room for improvement in advanced analytics, especially if the data is large, then it shows some performance issues."

"One area for product improvement is the user experience, particularly when navigating through screens."

"There are some transactions we have not been able to find through the dashboard."

More Oracle Advanced Analytics cons

"If you have one missing value in your dataset and this missing value belongs to a specific attribute and the attribute is a numeric attribute and there is only one missing data, whenever you import this data, the problem is that Weka cannot understand that this is a numeric field. It converts everything into a string, and there is no way to convert the string into numerical math. It's really very complicated."

"Documentation tends to lag and is sometimes inaccurate, but we have found that looking at the most recent version tends to show more accurate documents."

"For production, it's not the best option."

"If there are a lot more lines of code, then we should use another language."

"Help documentation could be more user friendly."

"I believe is there are a few newer algorithms that are not present in the Weka libraries. Whereas, for example, if I want to have a solution that involves deep learning, so I don't think that Weka has that capability. So in that case I have to use Python for ... predict any algorithms based on deep learning."

"The filter section lacks some specific transformation tools. If you want to change a variable from a numeric variable to a categorical variable, you don't have a feature that can enable you to change a variable from a numeric variable to a categorical variable."

"The visualization of Weka is subpar and could improve. Machine learning and visualization do not work well together. For example, we want to know how we can we delete empty cells or how can we fill in the empty cells without cleaning the data system and putting it together."

More Weka cons

Pricing and Cost Advice

"The solution is priced well."

"We use the free version now. My faculty is very small."

"As far as I know, Weka is a freeware tool, and I am not aware if they have an online solution or if it is a commercial product."

"Currently, I am using an open-source version so I don't know much about the price of this solution."

"The solution is free and open-source."

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Top Industries

By visitors reading reviews

No data available

Educational Organization

15%

University

13%

Comms Service Provider

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	2
Large Enterprise	2

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	2
Large Enterprise	5

Questions from the Community

What is your experience regarding pricing and costs for Oracle Advanced Analytics?

It is not about data, but mostly about cost, which is why I do not give it a nine or ten. It is costly.

What needs improvement with Oracle Advanced Analytics?

From my perspective, there is sometimes room for improvement in advanced analytics, especially if the data is large, then it shows some performance issues.

What is your primary use case for Oracle Advanced Analytics?

Some customers are implementing and working with Oracle Advanced Analytics, while some do not use it, so it depends on the customers. The implementation of Oracle Advanced Analytics is mostly for r...

What is your experience regarding pricing and costs for Weka?

My experience with pricing, setup cost, and licensing has been that we have received very good terms, and the setup cost and licensing have been easy to implement, with pricing exactly what we woul...

What needs improvement with Weka?

Weka can be improved in terms of not having to reboot nodes when operator versions need to be changed, but they are working toward that. Documentation tends to lag and is sometimes inaccurate, but ...

What is your primary use case for Weka?

My main use case for Weka is providing a high-speed shared file system on converged infrastructure. A specific example of how I use Weka for this shared file system is that we host user home direct...

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Product Reports

Oracle Advanced Analytics

Download Oracle Advanced Analytics product report

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Also Known As

OAA

No data available

Overview

Oracle Advanced Analytics provides powerful data customization and integration capabilities, making it suitable for businesses looking to enhance their analytics within Oracle ecosystems and beyond.

Oracle Advanced Analytics offers features like centralized reporting, predictive modeling, and integration with more than ten algorithms for data mining. Despite its strengths, challenges include complexity and licensing issues that affect ease of use and data processing. Users often deploy it to streamline data analysis, support cloud cost assessment, and integrate with SD-WAN environments for security-enhanced transitions. Its compatibility with OBI, ODI, and OBIA versions facilitates its adaptability in handling extensive data lakes.

What are the key features of Oracle Advanced Analytics?

Customization Abilities: Allows tailored analytics solutions to meet specific business requirements.
Integration: Compatible with Oracle and third-party tools, enhancing functionality.
User-Friendly Dashboards: Simplifies data exploration with intuitive visuals.
Predictive Modeling: Supports advanced analytics for better decision-making using SQL queries.
Data Mining Algorithms: Offers more than ten algorithms for comprehensive data mining.

What benefits should users expect?

Efficiency: Streamlines data insights with robust analytics.
Scalability: Manages large datasets effectively, provided performance enhancements are in place.
Adaptability: Supports diverse industries with its versatile applications.

Consulting firms employ Oracle Advanced Analytics for integrating secure transitions in SD-WAN environments, focusing on management and security aspects. In marketing, teams leverage it for projects that require analyzing multiple data sources to understand consumer behavior. It assists businesses in managing extensive data lakes, facilitating historical data analysis. Organizations benefit from its compatibility with Oracle tools like OBI, ODI, and OBIA, driving efficient operations in diverse industry contexts.

Oracle

Weka provides a user-friendly platform for data processing and classification with a no-code interface, visual tools, and diverse algorithms. Its robust GUI supports seamless enterprise data integration and efficient performance on large datasets.

Weka is known for its simplicity and comprehensive algorithm selection, making it a popular choice for data exploration, processing, clustering, and mining. The platform is user-friendly and caters to both beginners and advanced users, supporting machine learning algorithms like classification, J48, KNN, regression, and clustering. Users leverage Weka for anomaly detection, data cleansing, and visualization, often in research and educational settings. Despite its strengths, users seek better Python integration and enhanced deep learning support, as well as improvements in data visualization, installation, and scalable solutions for big data scenarios.

What key features does Weka offer?

Simplicity: Intuitive design with a no-code interface for rapid project execution
Visualization: Comprehensive tools to assist in data interpretation and decision-making
Algorithm Variety: Wide range of options for data processing and classification
Performance: Efficient handling of large datasets with seamless enterprise integration
User-Friendliness: Robust GUI that assists both beginners and experienced users

What benefits and ROI do users see?

Time-Saving: Quick deployment with intuitive interfaces reduces project timelines
Flexibility: Adaptable to both on-premise and cloud-based deployment environments
Comprehensive Mining: Extensive capabilities allow for exhaustive data exploration
Ease of Use: Design caters to a range of users, enhancing accessibility and productivity

Weka is used across industries for projects involving data exploration and machine learning, enhancing research and educational initiatives. It transforms decision trees and neural networks, catering to diverse deployment requirements.

Sample Customers

Orbitz, Marriott, SGS Life Science, Masdar, AlliantEnergy Corporation, British Standards Institute, Skybox Security, Triple PointTechnology, and Coca Cola.

Information Not Available

Oracle Advanced Analytics vs. Weka