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.
"One of the greatest advantages of KNIME is that it can be used by those without any coding experience. those with no coding background can use it."
"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."
"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."
"This solution is easy to use and it can be used to create any kind of model."
"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"RapidMiner for Windows is an excellent graphical tool for data science."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"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."
"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."
"The solution is stable."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the data stored there. RapidMiner offers a wider range of operators than other tools like Dataiku, making it a better option for my needs."
"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 good at visualization."
"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."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"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."
"The license is quite expensive for us."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"KNIME is not scalable."
"The price of this solution should be improved."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"Improve the online data services."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users."
"I think that they should make deep learning models easier."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"In the Mexican or Latin American market, it's kind of pricey."
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)