IBM SPSS Statistics vs KNIME vs SAS Enterprise Miner comparison

Cancel
You must select at least 2 products to compare!
IBM Logo
1,672 views|1,013 comparisons
Knime Logo
3,134 views|2,162 comparisons
SAS Logo
528 views|430 comparisons
Comparison Buyer's Guide
Executive Summary

We performed a comparison between IBM SPSS Statistics, KNIME, and SAS Enterprise Miner based on real PeerSpot user reviews.

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.
To learn more, read our detailed Data Mining Report (Updated: March 2024).
765,386 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The most valuable feature is its robust statistical analysis capabilities.""IBM SPSS Statistics depends on AI.""The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis.""Most of the product features are good but I particularly like the linear regression analysis.""It has the ability to easily change any variable in our research.""The software offers consistency across multiple research projects helping us with predictive analytics capabilities.""Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files.""The most valuable features are the small learning curve and its ability to hold a lot of data."

More IBM SPSS Statistics Pros →

"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript.""The product is open-source and therefore free to use.""It can handle an unlimited amount of data, which is the advantage of using Knime.""It's a coding-less opportunity to use AI. This is the major value for me.""Easy to use, stable, and powerful.""Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing.""Overall KNIME serves its purpose and does a good job.""I was able to apply basic algorithms through just dragging and dropping."

More KNIME Pros →

"he solution is scalable.""The technical support is very good.""Good data management and analytics.""The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them.""The setup is straightforward. Deployment doesn't take more than 30 minutes.""The solution is very good for data mining or any mining issues.""Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic.""The solution is able to handle quite large amounts of data beautifully."

More SAS Enterprise Miner Pros →

Cons
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering.""IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert.""The statistics should be more self-explanatory with detailed automated reports.""There is a learning curve; it's not very steep, but there is one.""The product should provide more ways to import data and export results that are user-friendly for high-level executives.""Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance.""It could allow adding color to data models to make them easier to interpret.""It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."

More IBM SPSS Statistics Cons →

"From the point of view of the interface, they can do a little bit better.""The documentation needs a proper rework. ​""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.""I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports.""The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data.""When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area.""It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved.""I would prefer to have more connectivity."

More KNIME Cons →

"The initial setup is challenging if doing it for the first time.""The product must provide better integration with cloud-native technologies.""While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system.""Virtualization could be much better.""The visualization of the models is not very attractive, so the graphics should be improved.""The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch.""The solution is much more complex than other options.""The ease of use can be improved. When you are new it seems a bit complex."

More SAS Enterprise Miner Cons →

Pricing and Cost Advice
  • "If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
  • "More affordable training for new staff members."
  • "Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."
  • "We think that IBM SPSS is expensive for this function."
  • "The price of this solution is a little bit high, which was a problem for my company."
  • "The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
  • "It's quite expensive, but they do a special deal for universities."
  • "The price of IBM SPSS Statistics could improve."
  • More IBM SPSS Statistics 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 →

  • "This solution is for large corporations because not everybody can afford it."
  • "The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
  • "The solution must improve its licensing models."
  • More SAS Enterprise Miner Pricing and Cost Advice →

    report
    Use our free recommendation engine to learn which Data Mining solutions are best for your needs.
    765,386 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
    Top Answer:While the pricing of the product may be higher, the accompanying service and features justify the investment. However… more »
    Top Answer:In some cases, the product takes time to load a large dataset. They could improve this particular area.
    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… more »
    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… more »
    Top Answer:I like the way the product visually shows the data pipeline.
    Top Answer:The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a… more »
    Top Answer:The product must provide better integration with cloud-native technologies.
    Ranking
    3rd
    out of 18 in Data Mining
    Views
    1,672
    Comparisons
    1,013
    Reviews
    8
    Average Words per Review
    537
    Rating
    8.6
    1st
    out of 18 in Data Mining
    Views
    3,134
    Comparisons
    2,162
    Reviews
    22
    Average Words per Review
    475
    Rating
    7.9
    6th
    out of 18 in Data Mining
    Views
    528
    Comparisons
    430
    Reviews
    2
    Average Words per Review
    310
    Rating
    8.5
    Comparisons
    Also Known As
    SPSS Statistics
    KNIME Analytics Platform
    Enterprise Miner
    Learn More
    Overview

    IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

    IBM SPSS Statistics Benefits

    Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:


    • Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.


    • Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.


    • Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle. 


    IBM SPSS Statistics Features


    • Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.


    • Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.


    • Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.


    Reviews from Real Users

    IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

    An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

    A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

    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.”

    SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.
    Sample Customers
    LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
    Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
    Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
    Top Industries
    REVIEWERS
    University46%
    Financial Services Firm17%
    Educational Organization4%
    Manufacturing Company4%
    VISITORS READING REVIEWS
    University16%
    Educational Organization12%
    Comms Service Provider11%
    Computer Software Company8%
    REVIEWERS
    University23%
    Comms Service Provider17%
    Retailer14%
    Government9%
    VISITORS READING REVIEWS
    Manufacturing Company12%
    Financial Services Firm11%
    Computer Software Company10%
    Educational Organization8%
    REVIEWERS
    Financial Services Firm44%
    Retailer22%
    University22%
    Media Company11%
    VISITORS READING REVIEWS
    Financial Services Firm22%
    University13%
    Educational Organization9%
    Insurance Company7%
    Company Size
    REVIEWERS
    Small Business26%
    Midsize Enterprise19%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    REVIEWERS
    Small Business29%
    Midsize Enterprise27%
    Large Enterprise45%
    VISITORS READING REVIEWS
    Small Business19%
    Midsize Enterprise14%
    Large Enterprise67%
    REVIEWERS
    Small Business21%
    Midsize Enterprise29%
    Large Enterprise50%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise10%
    Large Enterprise70%
    Buyer's Guide
    Data Mining
    March 2024
    Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: March 2024.
    765,386 professionals have used our research since 2012.