We performed a comparison between Oracle Advanced Analytics and Weka based on real PeerSpot user reviews.Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
"When needed, we will work closely with Oracle support and implement their workaround in our application."
"The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic."
"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."
"It doesn’t cost anything to use the product."
"Weka is a very nice tool, it needs very small requirements. If I want to implement something in Python, I need a lot of memory and space but Weka is very lightweight. Anyone can implement any kind of algorithm, and we can show the results immediately to the client using the one-page feature. The client always wants to know the story. They want the result."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"The performance, scalability and queries should be addressed, as well as the data distribution of certain data techniques."
"There are some transactions we have not been able to find through the dashboard."
"The product is good, but I would like it to work with big data. I know it has a Spark integration they could use to do analysis in clusters, but it's not so clear how to use it."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
"A few people said it became slow after a while."
"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."
Oracle Advanced Analytics 12c delivers parallelized in-database implementations of data mining algorithms and integration with open source R. Data analysts use Oracle Data Miner GUI and R to build and evaluate predictive models and leverage R packages and graphs. Application developers deploy Oracle Advanced Analytics models using SQL data mining functions and R. With the Oracle Advanced Analytics option, Oracle extends the Oracle Database to an sclable analytical platform that mines more data and data types, eliminates data movement, and preserves security to anticipate customer behavior, detect patterns, and deliver actionable insights. Oracle Big Data SQL adds new big data sources and Oracle R Advanced Analytics for Hadoop provides algorithms that run on Hadoop.
Oracle Advanced Analytics is ranked 7th in Data Mining with 2 reviews while Weka is ranked 3rd in Data Mining with 4 reviews. Oracle Advanced Analytics is rated 8.6, while Weka is rated 7.6. The top reviewer of Oracle Advanced Analytics writes "Helpful technical support, but performance and queries should be addressed". On the other hand, the top reviewer of Weka writes "Can plug in any machine learning algorithm and it works perfectly but needs better visualization ". Oracle Advanced Analytics is most compared with IBM SPSS Statistics, SAS Analytics, IBM SPSS Modeler, KNIME and SAS Enterprise Miner, whereas Weka is most compared with KNIME, IBM SPSS Statistics, IBM SPSS Modeler, SAS Analytics and SAS Enterprise Miner. See our Oracle Advanced Analytics vs. Weka report.
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