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: June 2026).

Oracle Advanced Analytics vs. Weka

June 2026

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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

4.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Weka

Ranking in Data Mining

4th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Anomaly Detection Tools (1st)

Mindshare comparison

As of June 2026, in the Data Mining category, the mindshare of Oracle Advanced Analytics is 4.8%, up from 4.2% compared to the previous year. The mindshare of Weka is 7.1%, down from 18.2% 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	4.8%
Other	88.1%

Data Mining

Featured Reviews

reviewer2174289

External Consultant at a consultancy with 51-200 employees

Customization and centralization improve efficiency despite complex user interface

The organizational context makes it difficult to deploy Oracle Advanced Analytics because we have all kinds of contract maintenance parties; however, the software installation itself is something we're used to doing, so that's no problem for us. It is not a really easy product to use, so you have to do a lot of configuration. The user interface is somewhat complex, and while they're working on that, for the end-user it is not really intuitive, so that could be improved. Currently, we are not using the predictive analytics capabilities, so I cannot say anything about it.

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Sanjay Charitesh Makam

Student at Rochester Institute of Technology

Data mining projects have become faster and visualization now guides our pattern discovery

Weka can be improved in some areas. As a one-year user, I can share my experiences. I have tried installing other packages into Weka using the inbuilt package manager or adding modern algorithms that I wish to apply to my data sets or data processing. I think Weka needs to improve in that and also in integrating Python into Weka, which would help users much more. I chose eight out of ten because we need improvements in Weka, such as installing inbuilt packages. Weka uses skips such as N+2 or N+4 and eight-node, which makes sense basically, but I think it should improve in the package attribute, such as configuring Python easily and adding modern algorithms into Weka more easily.

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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 Advanced Analytics helps us to steer the company, to create centralized reports and dashboards so that we're all using the same information, and we're not relying that much on Excel and different custom reporting solutions."

"The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic."

"Easy to use, simple, with a quick learning curve."

"Viewing the data on the Dashboard with charts is a great option this tool provides."

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

"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."

More Oracle Advanced Analytics pros

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

"My main recommendation is that if you want artificial intelligence, or machine learning, go for an easy and quick tool like Weka, otherwise, any language will have a more expensive entry cost."

"It’s pretty straightforward, it's user-friendly, it’s free, and with YouTube videos, online guides, and e-books on machine learning using Weka, you can quickly learn to use its good interface for data visualization, filtering, and creating different scenarios and instances."

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

"The path of machine learning in classification and clustering is useful. The GUI can get you results. No programming is needed. No need to write down your script first or send to your model or input your data."

"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."

"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."

"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."

More Weka pros

Cons

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

"I would like to see an improvement in the ease of implementing customized data sources and the like."

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

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

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

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

"Problems in handling huge data sets."

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

"The filter section lacks some specific transformation tools."

"I'm not sure if it's reliable. It's a little difficult to get results, especially if you are on some other programs like Tableau."

"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."

"A few people said it became slow after a while."

"Help documentation could be more user friendly."

"As students, if we use the largest data sets, I think Weka struggles with large data sets imported into it."

"Weka is not horizontally scalable. If I had to run a large dataset over Weka I would have to have a very large usage."

"In terms of scalability, I think Weka is not prepared to handle a large number of users."

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

19%

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	1

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	1
Large Enterprise	3

Questions from the Community

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

I am currently satisfied with the pricing for Oracle Advanced Analytics. It's a little bit high maybe, but I think it's acceptable.

What needs improvement with Oracle Advanced Analytics?

What is your primary use case for Oracle Advanced Analytics?

I currently use the solution just for gathering information, and I'm working on a side project detailing cloud costs. I downloaded the information to get some information about the situation. We ty...

What is your experience regarding pricing and costs for Weka?

My experience with pricing, setup cost, and licensing for Weka is that I think it's a fair price since we are using it academically, so it is completely free to download and use. The license is als...

What needs improvement with Weka?

What is your primary use case for Weka?

My main use case for Weka is data exploration and data processing and data mining. I can give a quick, specific example of how I've used Weka for data exploration or data processing: we have a subj...

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Product Reports

Oracle Advanced Analytics

May 2026

Download Oracle Advanced Analytics product report

Download Weka product report

May 2026

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