Compare KNIME vs. Weka

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Read 11 KNIME reviews.
25,270 views|19,094 comparisons
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Read 7 Weka reviews.
2,919 views|2,685 comparisons
Most Helpful Review
Hemant Addal
Find out what your peers are saying about KNIME vs. Weka and other solutions. Updated: January 2021.
456,812 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"This open-source product can compete with category leaders in ELT software.""The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes.""This solution is easy to use and especially good at data preparation and wrapping.""It's a coding-less opportunity to use AI. This is the major value for me.""This solution is easy to use and it can be used to create any kind of model.""All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function.""What I like the most is that it works almost out of the box with Random Forest and other Forest nodes.""It is very fast to develop solutions."

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"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.""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.""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.""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."

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Cons
"The ability to handle large amounts of data and performance in processing need to be improved.""I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script.""It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end.""There should be better documentation and the steps should be easier.""KNIME needs to provide more documentation and training materials, including webinars or online seminars.""The predefined workflows could use a bit of improvement.""The documentation is lacking and it could be better.""There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."

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"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.""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.""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.""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 there are a lot more lines of code, then we should use another language.""Not particularly user friendly.""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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Pricing and Cost Advice
"KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website.""The price of KNIME is quite reasonable and the designer tool can be used free of charge.""It's an open-source solution.""The price for Knime is okay.""At this time, I am using the free version of Knime."

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"Currently, I am using an open-source version so I don't know much about the price of this solution."

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Questions from the Community
Top Answer: This solution is easy to use and it can be used to create any kind of model.
Top Answer: The price of KNIME is quite reasonable and the designer tool can be used free of charge.
Top Answer: We are worried about the performance when it comes to using a lot of data that has many rows and columns. On the server-side, we are not sure whether KNIME can manage or handle large amounts of data… more »
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Ranking
1st
out of 15 in Data Mining
Views
25,270
Comparisons
19,094
Reviews
10
Average Words per Review
497
Rating
8.4
4th
out of 15 in Data Mining
Views
2,919
Comparisons
2,685
Reviews
7
Average Words per Review
1,001
Rating
7.3
Popular Comparisons
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Also Known As
KNIME Analytics Platform
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Knime
Weka
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Overview
KNIME is the leading open platform for data-driven innovation helping organizations to stay ahead of change. Use our open-source, enterprise-grade analytics platform to discover the potential hidden in your data, mine for fresh insights or predict new futures.Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
Offer
Learn more about KNIME
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Sample Customers
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Information Not Available
Top Industries
REVIEWERS
Comms Service Provider20%
Retailer20%
University20%
Energy/Utilities Company10%
VISITORS READING REVIEWS
Computer Software Company22%
Comms Service Provider19%
Educational Organization7%
Financial Services Firm6%
VISITORS READING REVIEWS
Comms Service Provider27%
Educational Organization18%
Computer Software Company16%
Financial Services Firm7%
Company Size
REVIEWERS
Small Business29%
Midsize Enterprise38%
Large Enterprise33%
No Data Available
Find out what your peers are saying about KNIME vs. Weka and other solutions. Updated: January 2021.
456,812 professionals have used our research since 2012.

KNIME is ranked 1st in Data Mining with 11 reviews while Weka is ranked 4th in Data Mining with 7 reviews. KNIME is rated 8.4, while Weka is rated 7.2. The top reviewer of KNIME writes "Has good machine learning and big data connectivity but the scheduler needs improvement ". On the other hand, the top reviewer of Weka writes "Relatively stable with excellent accuracy and there's no need to know coding". KNIME is most compared with Alteryx, RapidMiner, Dataiku Data Science Studio, H2O.ai and Databricks, whereas Weka is most compared with IBM SPSS Statistics, IBM SPSS Modeler, SAS Analytics, SAS Enterprise Miner and Oracle Advanced Analytics. See our KNIME vs. Weka report.

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