We performed a comparison between Splunk User Behavior Analytics and Weka based on real PeerSpot user reviews.
Find out in this report how the two User Entity Behavior Analytics (UEBA) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It's easily scalable."
"The solution is extremely scalable. Our customers are regularly scaling up after installing Splunk."
"The solution is definitely scalable."
"This intelligent user behavior analytics package is easy to configure and use while remaining feature filled."
"The most valuable feature is being able to take data and put it into other systems so that we could see the output, and to see where we need to apply our focus."
"Because of some of the visualizations that we utilize, we are able to understand strange, unusual traffic on our networks."
"This is a good security product."
"The solution's most valuable feature is Splunk queries, which allow us to query the logs and analyze the attack vectors."
"With clustering, if it's a yes, it's a yes, if it's a no, it's a no. It gives you a 100% level of accuracy of a model that has been trained, and that is in most cases, usually misleading. Classification is highly valuable when done as opposed to clustering."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"It is a stable product."
"The interface is very good, and the algorithms are the very best."
"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."
"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."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"Weka eliminates the need for coding, allowing you to easily set parameters and complete the majority of the machine learning task with just a few clicks."
"It would be good if the solution had an analytics tool that allowed us to analyze the data without writing specific queries."
"In the future I would like to see simplified statistics and analytical threats."
"We'd like the ability to do custom searches."
"If the price was lowered and the setup process was less complex, I would consider rating it higher."
"We want to have an automated system for bot hunting that enables us to detect anomalies predictively based on historical data. It would be helpful if Splunk included process mining as an alternative option. We have a threat workflow, but it would be useful if we could supplement that with some process mining capabilities over time."
"I would like improved downward integration with other tools such as McAfee and other GCP solutions."
"The solution is much more expensive than relative competitors like ArcSight or LogRhythm. It makes it hard to sell to customers sometimes."
"It could be easier to scale the solution if you are using it on-premise, not in the cloud."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
"If there are a lot more lines of code, then we should use another language."
"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."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
"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."
"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."
"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."
"Not particularly user friendly."
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Splunk User Behavior Analytics is ranked 2nd in User Entity Behavior Analytics (UEBA) with 18 reviews while Weka is ranked 2nd in Data Mining with 14 reviews. Splunk User Behavior Analytics is rated 8.2, while Weka is rated 7.6. The top reviewer of Splunk User Behavior Analytics writes "Easy to configure and easy to use solution that integrates with many applications and scripts ". On the other hand, the top reviewer of Weka writes "Open source, good for basic data mining use cases except for the visualization results". Splunk User Behavior Analytics is most compared with Darktrace, Microsoft Defender for Identity, IBM Security QRadar, Cynet and Dtex Systems, whereas Weka is most compared with KNIME, IBM SPSS Statistics, IBM SPSS Modeler, Oracle Advanced Analytics and SAS Enterprise Miner. See our Splunk User Behavior Analytics vs. Weka report.
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