Compare IBM SPSS Modeler vs. KNIME

IBM SPSS Modeler is ranked 1st in Data Mining with 23 reviews while KNIME is ranked 2nd in Data Mining with 9 reviews. IBM SPSS Modeler is rated 8.0, while KNIME is rated 8.6. The top reviewer of IBM SPSS Modeler writes "Ease of use, the user interface, is the best part; the ability to customize streams with R and Python is useful". On the other hand, the top reviewer of KNIME writes "Our average record size was around 10 million records. If we have bigger data, we can opt for a Big Data extension for Hadoop, Spark, etc". IBM SPSS Modeler is most compared with KNIME, Alteryx and IBM Watson Studio, whereas KNIME is most compared with Alteryx, RapidMiner and Weka. See our IBM SPSS Modeler vs. KNIME report.
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IBM SPSS Modeler Logo
9,664 views|7,402 comparisons
KNIME Logo
20,247 views|15,789 comparisons
Most Helpful Review
Find out what your peers are saying about IBM SPSS Modeler vs. KNIME and other solutions. Updated: September 2019.
366,090 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
Automated modelling, classification, or clustering are very useful.A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly.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.It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler.New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data.We use analytics with the visual modeling capability to leverage productivity improvements.It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale itThe ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that.

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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.We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics.Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server.

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Cons
Customer support is hard to contact.It is not integrated with Qlik, Tableau, and Power BI.Expensive to deploy solutions. You need to buy an extra deployment unit.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.The standard package (personal) is not supported for database connection.Unstructured data is not appropriate for SPSS Modeler.Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization.I think mapping for geographic data would also be a really great thing to be able to use.

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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.​The 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.I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something.I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports.

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Pricing and Cost Advice
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.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.It is a huge increase to time savings.If you are in a university and the license is free then you can use the tool without any charges, which is good.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.

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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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report
Use our free recommendation engine to learn which Data Mining solutions are best for your needs.
366,090 professionals have used our research since 2012.
Ranking
1st
out of 16 in Data Mining
Views
9,664
Comparisons
7,402
Reviews
23
Average Words per Review
458
Avg. Rating
8.1
2nd
out of 16 in Data Mining
Views
20,247
Comparisons
15,789
Reviews
9
Average Words per Review
357
Avg. Rating
8.6
Top Comparisons
Compared 18% of the time.
Compared 13% of the time.
Compared 40% of the time.
Compared 14% of the time.
Compared 8% of the time.
Also Known As
SPSS ModelerKNIME Analytics Platform
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IBM
Knime
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.

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https://www.ibm.com/products/spss-modeler/pricing
 
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https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947


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.
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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 TurkeyInfocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Top Industries
REVIEWERS
Financial Services Firm25%
Manufacturing Company15%
Healthcare Company10%
Government10%
VISITORS READING REVIEWS
Financial Services Firm21%
Software R&D Company16%
University11%
Government5%
VISITORS READING REVIEWS
Comms Service Provider20%
Financial Services Firm13%
Software R&D Company10%
Manufacturing Company9%
Company Size
REVIEWERS
Small Business30%
Midsize Enterprise11%
Large Enterprise59%
REVIEWERS
Small Business20%
Midsize Enterprise30%
Large Enterprise50%
VISITORS READING REVIEWS
Small Business14%
Midsize Enterprise2%
Large Enterprise84%
Find out what your peers are saying about IBM SPSS Modeler vs. KNIME and other solutions. Updated: September 2019.
366,090 professionals have used our research since 2012.
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.
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