We performed a comparison between KNIME 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."KNIME is easy to learn."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"We have found KNIME valuable when it comes to its visualization."
"We can deploy the solution in a cluster as well."
"I would rate the stability of KNIME a ten out of ten."
"The solution is good for teaching, since there is no need to code."
"It has allowed us to easily implement advanced analytics into various processes."
"I've never had any problems with stability."
"Working with complicated algorithms in huge datasets is really easy in Weka."
"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."
"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 is a stable product."
"It doesn’t cost anything to use the product."
"In Weka, anyone can access the program without being a programmer, which is a good feature since the entry cost is very low."
"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."
"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."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
"The pricing needs improvement."
"It could be easier to use."
"In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them."
"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
"Not particularly user friendly."
"While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results."
"Weka could be more stable."
"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."
"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."
"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."
"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."
KNIME is ranked 1st in Data Mining with 50 reviews while Weka is ranked 2nd in Data Mining with 14 reviews. KNIME is rated 8.2, while Weka is rated 7.6. The top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". On the other hand, the top reviewer of Weka writes "Open source, good for basic data mining use cases except for the visualization results". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Microsoft Azure Machine Learning Studio, whereas Weka is most compared with IBM SPSS Statistics, IBM SPSS Modeler, Oracle Advanced Analytics, SAS Analytics and Splunk User Behavior Analytics. See our KNIME vs. Weka report.
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