IBM SPSS Modeler vs KNIME comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between IBM SPSS Modeler and KNIME based on real PeerSpot user reviews.

Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed IBM SPSS Modeler vs. KNIME Report (Updated: March 2024).
763,955 professionals have used our research since 2012.
Q&A Highlights
Question: What is the biggest difference between IBM SPSS Modeler and KNIME?
Answer: The main difference lies in the community that has KNIME because the additional modules serve a multitude of different jobs from image processing, management of ssh file systems to chemical molecule calculations.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms.""I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation.""​It works fine. I have not had any stability issues; it is always up.​""It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful.""Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms.""A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly.""IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level.""Compared to other tools, the product works much easier to analyze data without coding."

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"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.""It has allowed us to easily implement advanced analytics into various processes.""I would rate the stability of KNIME a ten out of ten.""It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript.""This solution is easy to use and it can be used to create any kind of model.""Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time.""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.""What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."

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Cons
"​I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities.​""I think mapping for geographic data would also be a really great thing to be able to use.""It is not integrated with Qlik, Tableau, and Power BI.""It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler.""C&DS will not meet our scalability needs.""I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it.""I can say the solution is outdated.""When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."

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"​The data visualization part is the area most in need of improvement.""It could input more data acquisitions from other sources and it is difficult to combine with Python.""They should look at other vendors like Alteryx that are more user friendly and modern.""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.""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.""The pricing needs improvement.""System resource usage. Knime will occupy total system RAM size and other applications will hang.""The documentation is lacking and it could be better."

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Pricing and Cost Advice
  • "Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."
  • "If you are in a university and the license is free then you can use the tool without any charges, which is good."
  • "It is a huge increase to time savings."
  • "The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."
  • "When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."
  • "It got us a good amount of money with quick and efficient modeling."
  • "$5,000 annually."
  • "This tool, being an IBM product, is pretty expensive."
  • More IBM SPSS Modeler 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 →

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    Answers from the Community
    EzzAbdelfattah
    Zachary Weber - PeerSpot reviewerZachary Weber
    User

    KNIME. It free, open-source, and you can plug in Java, Python, R, and Matlab. The community is awesome.

    Laurence Moseley - PeerSpot reviewerLaurence Moseley
    Real User

    I used IBM Modeler several years ago and found it to be effective, but expensive. Fortunately, it was for a commercially funded contract.
    For KNIME I have only used it for experimental purposes and found it rather cumbersome but powerful. It is also more cost-effective.
    I found RapidMiner more intuitive to learn. However, there is so much choice nowadays that it is difficult to be definitive. In my experience, it largely depended on the quality of the add-on extensions. Clearly, though, at least in universities, the cost is a significant factor.

    reviewer1070595 - PeerSpot reviewerreviewer1070595 (Senior Statistical Consultant at a financial services firm with 501-1,000 employees)
    Consultant

    I am not familiar with KNIME, but the main difference is KNIME is open-source and free.

    Questions from the Community
    Top Answer:Compared to other tools, the product works much easier to analyze data without coding.
    Top Answer:The platform's cloud version needs improvements. The process to access workflow could be user-friendly. It could be easier to log in and manage security levels. Additionally, it needs to be more… more »
    Top Answer: I've never had any problems with stability.
    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:In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could… more »
    Ranking
    4th
    out of 18 in Data Mining
    Views
    1,782
    Comparisons
    1,420
    Reviews
    6
    Average Words per Review
    372
    Rating
    7.3
    1st
    out of 18 in Data Mining
    Views
    3,134
    Comparisons
    2,162
    Reviews
    22
    Average Words per Review
    475
    Rating
    7.9
    Comparisons
    Also Known As
    SPSS Modeler
    KNIME Analytics Platform
    Learn More
    IBM
    Video Not Available
    Overview

    IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

    Buy
    https://www.ibm.com/products/spss-modeler/pricing
     
    Sign up for the trial
    https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947


    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.”

    Sample Customers
    Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey
    Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
    Top Industries
    REVIEWERS
    University23%
    Financial Services Firm17%
    Manufacturing Company14%
    Government9%
    VISITORS READING REVIEWS
    Educational Organization16%
    Financial Services Firm10%
    Computer Software Company9%
    University8%
    REVIEWERS
    University24%
    Comms Service Provider18%
    Retailer15%
    Government9%
    VISITORS READING REVIEWS
    Manufacturing Company12%
    Financial Services Firm11%
    Computer Software Company9%
    Educational Organization8%
    Company Size
    REVIEWERS
    Small Business19%
    Midsize Enterprise10%
    Large Enterprise71%
    VISITORS READING REVIEWS
    Small Business23%
    Midsize Enterprise14%
    Large Enterprise63%
    REVIEWERS
    Small Business30%
    Midsize Enterprise24%
    Large Enterprise46%
    VISITORS READING REVIEWS
    Small Business19%
    Midsize Enterprise14%
    Large Enterprise68%
    Buyer's Guide
    IBM SPSS Modeler vs. KNIME
    March 2024
    Find out what your peers are saying about IBM SPSS Modeler vs. KNIME and other solutions. Updated: March 2024.
    763,955 professionals have used our research since 2012.

    IBM SPSS Modeler is ranked 4th in Data Mining with 6 reviews while KNIME is ranked 1st in Data Mining with 22 reviews. IBM SPSS Modeler is rated 8.0, while KNIME is rated 8.2. The top reviewer of IBM SPSS Modeler writes "Useful visual programming, minimal configuration required, and overall powerful". On the other hand, the top reviewer of KNIME writes "Allows you to easily tidy up your data, make lots of changes internally, and has good machine learning". IBM SPSS Modeler is most compared with Microsoft Power BI, RapidMiner, IBM SPSS Statistics, Alteryx and Microsoft Azure Machine Learning Studio, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Microsoft Azure Machine Learning Studio. See our IBM SPSS Modeler vs. KNIME report.

    See our list of best Data Mining vendors and best Data Science Platforms vendors.

    We monitor all Data Mining 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.