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."This is a good security product."
"This intelligent user behavior analytics package is easy to configure and use while remaining feature filled."
"We are really pleased with Splunk and its features. It would be practically impossible to function without it. To provide a general overview of the system, it's important to note that the standard log files are currently around 250 gigabytes per day. It would be impossible to manually walk through these logs by hand, which is why automation is essential."
"Splunk is more user-friendly than some competing solutions we tried."
"The solution is definitely scalable."
"The solution is extremely scalable. Our customers are regularly scaling up after installing Splunk."
"The solution is fast, flexible, and easy to use."
"The most valuable feature is the ability to search through a large amount of data."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
"Working with complicated algorithms in huge datasets is really easy in Weka."
"It is a stable product."
"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."
"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 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."
"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."
"The interface is very good, and the algorithms are the very best."
"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."
"It could be easier to scale the solution if you are using it on-premise, not in the cloud."
"Currently, a lot of network operations need improvement. We still need people to handle incidents. Our vision is to leverage status and convert it directly from the network devices. It would be ideal if we could take action using APIs and API code and remove manual processes."
"The initial setup was complex because some of the configurations that we required needed customization."
"In the future I would like to see simplified statistics and analytical threats."
"We'd like the ability to do custom searches."
"The correlation engine should have persistent and definable rules."
"I'm not aware of any lacking features."
"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."
"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 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."
"Weka could be more stable."
"If there are a lot more lines of code, then we should use another language."
"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."
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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.
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.
