Compare KNIME vs. RapidMiner

KNIME is ranked 2nd in Data Science Platforms with 10 reviews while RapidMiner is ranked 5th in Data Science Platforms with 8 reviews. KNIME is rated 8.2, while RapidMiner is rated 8.2. 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 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 Alteryx, RapidMiner and Weka, whereas RapidMiner is most compared with KNIME, Alteryx and H2O.ai. See our KNIME vs. RapidMiner report.
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KNIME Logo
Read 10 KNIME reviews.
22,954 views|17,868 comparisons
RapidMiner Logo
9,254 views|7,709 comparisons
Most Helpful Review
Find out what your peers are saying about KNIME vs. RapidMiner and other solutions. Updated: January 2020.
399,540 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.This solution is easy to use and especially good at data preparation and wrapping.It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop.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.Clear view of the data at every step of ETL process enables changing the flow as needed.We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders.The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine.Easy to connect with every database: We use queries from SQL, Redshift, Oracle.

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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 GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model.The most valuable feature is what the product sets out to do, which is extracting information and data.The most valuable features are the Binary classification and Auto Model.RapidMiner is very easy to use.The documentation for this solution is very good, where each operator is explained with how to use it.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.

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Cons
The ability to handle large amounts of data and performance in processing need to be improved.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.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.The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R).The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily.‚ÄčThe data visualization part is the area most in need of improvement.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.Data visualization needs improvement.

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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.It would be helpful to have some tutorials on communicating with Python.The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator.A great product but confusing in some way with regard to the user interface and integration with other tools.RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models.I would like to see all users have access to all of the deep learning models, and that they can be used easily.The price of this solution should be improved.The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade.

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Pricing and Cost Advice
KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required.

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The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license.Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year.I used an educational license for this solution, which is available free of charge.

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report
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399,540 professionals have used our research since 2012.
Ranking
2nd
Views
22,954
Comparisons
17,868
Reviews
10
Average Words per Review
352
Avg. Rating
8.2
5th
Views
9,254
Comparisons
7,709
Reviews
8
Average Words per Review
592
Avg. Rating
8.3
Top Comparisons
Compared 42% of the time.
Compared 13% of the time.
Compared 7% of the time.
Compared 35% of the time.
Compared 21% of the time.
Compared 6% of the time.
Also Known As
KNIME Analytics Platform
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Knime
RapidMiner
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.

RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.

Offer
Learn more about KNIME
Learn more about RapidMiner
Sample Customers
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AGPayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Top Industries
VISITORS READING REVIEWS
Software R&D Company25%
Comms Service Provider16%
Financial Services Firm9%
Manufacturing Company7%
VISITORS READING REVIEWS
Software R&D Company20%
University14%
Comms Service Provider12%
Manufacturing Company9%
Company Size
REVIEWERS
Small Business21%
Midsize Enterprise36%
Large Enterprise43%
VISITORS READING REVIEWS
Small Business18%
Midsize Enterprise1%
Large Enterprise81%
REVIEWERS
Small Business55%
Midsize Enterprise9%
Large Enterprise36%
VISITORS READING REVIEWS
Small Business24%
Midsize Enterprise2%
Large Enterprise74%
Find out what your peers are saying about KNIME vs. RapidMiner and other solutions. Updated: January 2020.
399,540 professionals have used our research since 2012.
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