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.
"This solution is easy to use and especially good at data preparation and wrapping."
"I've tried to utilize KNIME to the fullest extent possible to replace Excel."
"It's a very powerful and simple tool to use."
"Overall KNIME serves its purpose and does a good job."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics."
"KNIME is easy to learn."
"Easy to use, stable, and powerful."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The data science, collaboration, and IDN are very, very strong."
"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."
"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."
"RapidMiner for Windows is an excellent graphical tool for data science."
"The best part of RapidMiner is efficiency."
"KNIME could improve when it comes to large data markets."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."
"The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"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."
"KNIME's documentation is not strong."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"Improve the online data services."
"The price of this solution should be improved."
"I would like to see more integration capabilities."
"RapidMiner can improve deep learning by enhancing the features."
"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"It would be helpful to have some tutorials on communicating with Python."
KNIME is ranked 4th in Data Science Platforms with 50 reviews while RapidMiner is ranked 6th in Data Science Platforms with 20 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 "A no-code tool that helps to build machine learning models ". KNIME is most compared with Microsoft Power BI, Alteryx, Dataiku, Weka and IBM SPSS Modeler, whereas RapidMiner is most compared with Alteryx, Dataiku, 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)