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."The most valuable feature is the ability to search through a large amount of data."
"Because of some of the visualizations that we utilize, we are able to understand strange, unusual traffic on our networks."
"It's easily scalable."
"It's straightforward in terms of configuration and troubleshooting and log management and monitoring as well. These are the edge points in addition to it being a modular solution where you can capitalize on your current licenses with extra licensing models, which can match the customer's business requirement and it can help the customer to design or to actually plan for their own roadmap."
"Splunk is more user-friendly than some competing solutions we tried."
"This intelligent user behavior analytics package is easy to configure and use while remaining feature filled."
"This is a good security product."
"It is a solution that helps test and measure customer satisfaction."
"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."
"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 mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"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."
"The interface is very good, and the algorithms are the very best."
"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 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."
"If the price was lowered and the setup process was less complex, I would consider rating it higher."
"I'm not aware of any lacking features."
"The price of Splunk UBA is too high."
"They should work to add more built-in correlation searches and more use cases based on worldwide customer experiences. They need more ready-made use cases."
"The ability to do more complicated data investigation would be a welcome addition for pros, though the functionality now gives most people what they need."
"The correlation engine should have persistent and definable rules."
"I would like improved downward integration with other tools such as McAfee and other GCP solutions."
"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."
"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."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"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."
"A few people said it became slow after a while."
"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."
"In terms of scalability, I think Weka is not prepared to handle a large number of users."
"Not particularly user friendly."
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Splunk User Behavior Analytics is ranked 2nd in User Entity Behavior Analytics (UEBA) with 17 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, Varonis Datalert and Securonix UEBA, 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.
We monitor all User Entity Behavior Analytics (UEBA) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
