We compared RapidMiner and KNIME based on our user's reviews in several parameters.
RapidMiner stands out for its advanced machine learning algorithms, extensive pre-built models, and active community support, while KNIME is praised for its easy-to-use interface, extensive library of nodes, and excellent customer service. Users note that RapidMiner offers more flexibility and scalability, while KNIME is considered more user-friendly. Both have affordable pricing and positive ROI, but users suggest improvements in documentation and performance for RapidMiner, and enhancements in interface, tutorials, and advanced features for KNIME.
Features: RapidMiner stands out for its user-friendly interface, intuitive data visualization, powerful data preparation and analysis capabilities, and advanced machine learning algorithms. On the other hand, KNIME is praised for its ease of use, powerful data manipulation, extensive library of nodes, and ability to handle big data. Both offer excellent visualizations and seamless integration with other tools and platforms.
Pricing and ROI: In terms of setup cost, RapidMiner offers affordable and flexible pricing options, with a straightforward and transparent licensing approach. On the other hand, KNIME has minimal setup cost and a flexible licensing approach that accommodates the needs of different users and organizations., Based on user feedback, RapidMiner demonstrated positive ROI with increased efficiency, cost savings, and improved decision-making. KNIME also showed favorable ROI with users satisfied with the platform's value.
Room for Improvement: Users have mentioned that RapidMiner could benefit from better documentation and tutorials to help beginners navigate the platform more easily. Additionally, the user interface could be more intuitive and user-friendly. Some users have also suggested improved performance for larger datasets. On the other hand, KNIME users have expressed a desire for a more intuitive interface, better documentation, and tutorials. They have also mentioned performance and speed optimizations, as well as integrating more advanced analytics and machine learning capabilities.
Deployment and customer support: The user reviews suggest that the duration required for establishing a new tech solution can vary between RapidMiner and KNIME. Some RapidMiner users reported spending three months on deployment and an additional week on setup, while others mentioned needing a week for both deployment and setup. KNIME users also had similar experiences, with some spending three months on deployment and a week on setup, while others only needed a week for both tasks. It is important to consider the context in which these terms are used to accurately analyze the timeframes., RapidMiner and KNIME both offer excellent customer service. Users appreciate RapidMiner's helpfulness and responsiveness, while KNIME's support team is praised for their prompt and reliable assistance.
The summary above is based on 27 interviews we conducted recently with RapidMiner and KNIME users. To access the review's full transcripts, download our report.
"I know I don't use it to its full capacity, but I love the Rule Engine feature. It has allowed me to create lookup tables on the fly and break down text fields into quantifiable data."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"The most useful features are the readily available extensions that speed up the work."
"It is a stable solution...It is a scalable solution."
"From a user-friendliness perspective, it's a great tool."
"The solution is good for teaching, since there is no need to code."
"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."
"Stability is excellent. I would give it a nine out of ten."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"The best part of RapidMiner is efficiency."
"The data science, collaboration, and IDN are very, very strong."
"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"One thing to consider is that the prebuilt nodes may not always be a perfect fit for your specific needs, although most of the time, they work quite well."
"KNIME's licensing and data management aren't as straightforward relative to Alteryx. Alteryx's tools are more sophisticated, so you need fewer to use it compared to KNIME. I think tab implementation could be easier, too."
"The ability to handle large amounts of data and performance in processing need to be improved."
"There should be better documentation and the steps should be easier."
"KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile."
"KNIME's documentation is not strong."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
"KNIME is not scalable."
"I would like to see more integration capabilities."
"If they could include video tutorials, people would find that quite helpful."
"In the Mexican or Latin American market, it's kind of pricey."
"RapidMiner can improve deep learning by enhancing the features."
"The price of this solution should be improved."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
KNIME is ranked 4th in Data Science Platforms with 50 reviews while RapidMiner is ranked 7th in Data Science Platforms with 19 reviews. KNIME is rated 8.2, while RapidMiner is rated 8.6. 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 RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". KNIME is most compared with Microsoft Power BI, Alteryx, Weka, Dataiku Data Science Studio and IBM SPSS Modeler, whereas RapidMiner is most compared with Alteryx, Dataiku Data Science Studio, Tableau, Microsoft Azure Machine Learning Studio and IBM SPSS Modeler. See our KNIME vs. RapidMiner report.
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Of those three you should consider alteryx, it saves time in ETL a lot, Alteryx is better at handling large data sets tan Knime and RapidMiner. But please also consider Dataiku... Up to 3 users it's free ;o)