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Knime Logo
10,966 views|7,554 comparisons
93% willing to recommend
RapidMiner Logo
5,569 views|4,500 comparisons
95% willing to recommend
Comparison Buyer's Guide
Executive Summary
Updated on Mar 6, 2024

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.

To learn more, read our detailed KNIME vs. RapidMiner Report (Updated: March 2024).
769,479 professionals have used our research since 2012.
Q&A Highlights
Question: Which solution provides the best ROI: KNIME, Alteryx or RapidMiner?
Answer: I'd suggest checking out the new Actable AI as well. It has a better AutoML and a lot more advanced features like Causal ML.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server.""KNIME is quite scalable, which is one of the most important features that we found.""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.""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 can handle an unlimited amount of data, which is the advantage of using Knime.""We can deploy the solution in a cluster as well.""This open-source product can compete with category leaders in ELT software.""It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea."

More KNIME Pros →

"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations.""RapidMiner is very easy to use.""We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space.""The data science, collaboration, and IDN are very, very strong.""I've been using a lot of components from the Strategic Extension and Python Extension.""The documentation for this solution is very good, where each operator is explained with how to use it.""It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive.""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."

More RapidMiner Pros →

Cons
"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.""The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon.""KNIME could improve when it comes to large data markets.""There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger.""From the point of view of the interface, they can do a little bit better.""I would prefer to have more connectivity.""The most difficult part of the solution revolves around its areas concerning machine learning and deep learning.""Data visualization needs improvement."

More KNIME Cons →

"I would like to see all users have access to all of the deep learning models, and that they can be used easily.""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.""I would like to see more integration capabilities.""I would appreciate improvements in automation and customization options to further streamline processes.""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.""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.""RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models.""In the Mexican or Latin American market, it's kind of pricey."

More RapidMiner Cons →

Pricing and Cost Advice
  • "It is free of cost. It is GNU licensed."
  • "KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
  • "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."
  • "This is an open-source solution that is free to use."
  • More KNIME Pricing and Cost Advice →

  • "I used an educational license for this solution, which is available free of charge."
  • "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."
  • "The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."
  • "For the university, the cost of the solution is free for the students and teachers."
  • More RapidMiner Pricing and Cost Advice →

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    Answers from the Community
    AshokPai
    AltanAtabarut - PeerSpot reviewerAltanAtabarut
    Real User

    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)







    Questions from the Community
    Top Answer:Since KNIME is a no-code platform, it is easy to work with.
    Top Answer:We're using the free academic license just locally. I went for KNIME because they have a free academic license. And to be honest, I never bothered to check the prices.
    Top Answer:KNIME is not good at visualization. I would like to see NLQ (Natural language query) and automated visualizations added to KNIME.
    Top Answer: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.
    Top Answer:I would appreciate improvements in automation and customization options to further streamline processes. Additionally, it can be challenging to structure formulas and access certain metrics, requiring… more »
    Ranking
    4th
    Views
    10,966
    Comparisons
    7,554
    Reviews
    21
    Average Words per Review
    501
    Rating
    7.9
    6th
    Views
    5,569
    Comparisons
    4,500
    Reviews
    5
    Average Words per Review
    346
    Rating
    8.2
    Comparisons
    Microsoft Power BI logo
    Compared 20% of the time.
    Alteryx logo
    Compared 13% of the time.
    Weka logo
    Compared 8% of the time.
    IBM SPSS Modeler logo
    Compared 5% of the time.
    Also Known As
    KNIME Analytics Platform
    Learn More
    Overview

    KNIME is an open-source analytics software used for creating data science that is built on a GUI based workflow, eliminating the need to know code. The solution has an inherent modular workflow approach that documents and stores the analysis process in the same order it was conceived and implemented, while ensuring that intermediate results are always available. 

    KNIME supports Windows, Linux, and Mac operating systems and is suitable for enterprises of all different sizes. With KNIME, you can perform functions ranging from basic I/O to data manipulations, transformations and data mining. It consolidates all the functions of the entire process into a single workflow. The solution covers all main data wrangling and machine learning techniques, and is based on visual programming.

    KNIME Features

    KNIME has many valuable key features. Some of the most useful ones include:

    • Scalability through data handling (intelligent automatic caching of data in the background while maximizing throughput performance)
    • High extensibility via a well-defined API for plugin extensions
    • Intuitive user interface
    • Import/export of workflows
    • Parallel execution on multi-core systems
    • Command line version for "headless" batch executions
    • Activity dashboard
    • Reporting & statistics
    • Third-party integrations
    • Workflow management
    • Local automation
    • Metanode linking
    • Tool blending
    • Big Data extensions

    KNIME Benefits

    There are many benefits to implementing KNIME. Some of the biggest advantages the solution offers include:

    • Integrated Deployment: KNIME’s integrated deployment moves both the selected model, and the entire data model preparation process into production simply and automatically, allowing for continuous optimization in production and also saving time because it eliminates error.
    • Elastic and Hybrid Execution: KNIME’s elastic and hybrid executions helps you reduce costs while covering periods of high demand, dynamically.
    • Metadata Mapping: KNIME enables complete metadata mapping of all aspects of your workflow. In addition, KNIME offers blueprint workflows for documenting the nodes, data sources, and libraries used, as well as runtime information.
    • Guided Analytics: KNIME’s guided analytics applications can be customized based on reusable components.
    • Powerful analytics, local automation, and workflow difference: KNIME uses advanced predictive and machine learning algorithms to provide you with the analytics you need. In combination with powerful analytics, KNIME’s automation capabilities and workflow difference prepare your organization with the tools you need to make better business decisions.
    • Supports enterprise-wide data science practices: The deployment and management functionalities of KNIME make it easy to productionize data science applications and services, and deliver usable, reliable, and reproducible insights for the business.
    • Helps you leverage insights gained from your data: Using KNIME ensures the data science process immediately reflects changing requirements or new insights.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot users currently using the KNIME solution.

    An Emeritus Professor at a university says, “It can read many different file formats. It can very easily tidy up your data, deleting blank rows, and deleting rows where certain columns are missing. It allows you to make lots of changes internally, which you do using JavaScript to put in the conditional. 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.”

    Benedikt S., CEO at SMH - Schwaiger Management Holding GmbH, explains, “All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function. Technical support has been extremely responsive so far. The solution has a very strong and supportive community that shares information and helps each other troubleshoot. The solution is very stable. The initial setup is pretty simple and straightforward.”

    Piotr Ś., Test Engineer at ProData Consult, says, “What I like the most is that it works almost out of the box with Random Forest and other Forest nodes.”

    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.

    Sample Customers
    Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
    PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
    Top Industries
    REVIEWERS
    University25%
    Comms Service Provider17%
    Retailer14%
    Government8%
    VISITORS READING REVIEWS
    Manufacturing Company12%
    Financial Services Firm11%
    Computer Software Company9%
    Educational Organization8%
    REVIEWERS
    University46%
    Educational Organization8%
    Engineering Company8%
    Wireless Company8%
    VISITORS READING REVIEWS
    University11%
    Computer Software Company10%
    Educational Organization10%
    Manufacturing Company9%
    Company Size
    REVIEWERS
    Small Business28%
    Midsize Enterprise26%
    Large Enterprise46%
    VISITORS READING REVIEWS
    Small Business19%
    Midsize Enterprise14%
    Large Enterprise67%
    REVIEWERS
    Small Business50%
    Midsize Enterprise20%
    Large Enterprise30%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise13%
    Large Enterprise67%
    Buyer's Guide
    KNIME vs. RapidMiner
    March 2024
    Find out what your peers are saying about KNIME vs. RapidMiner and other solutions. Updated: March 2024.
    769,479 professionals have used our research since 2012.

    KNIME is ranked 4th in Data Science Platforms with 50 reviews while RapidMiner is ranked 6th 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, Dataiku Data Science Studio, Weka 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.

    See our list of best Data Science Platforms vendors.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.