KNIME vs SAS Analytics comparison

Knime and SAS are both solutions in the Data Mining category. Knime is ranked #1 with an average rating of 8.0, while SAS is ranked #5 with an average rating of 9.0. Knime holds a 24.6% mindshare in DM, compared to SAS’s 7.3% mindshare. Additionally, 94% of Knime users are willing to recommend the solution, compared to 94% of SAS users who would recommend it.

KNIME

Read 60 KNIME reviews

10,613 Views
1,592 Comparison Views

94% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

555 Views
555 Comparison Views

94% willing to recommend

KNIME

SAS Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on May 21, 2025

SAS Analytics and KNIME are both established competitors in the data analytics segment. KNIME has an advantage due to its open-source nature, offering flexibility and a better value for its pricing model.

Features: SAS Analytics provides enterprise-ready statistical analysis, advanced forecasting tools, and data visualization, ideal for large enterprises managing complex data. KNIME is noteworthy for its intuitive data blending, machine learning capabilities, and workflow automation, which benefit smaller businesses or those preferring customizable solutions.

Room for Improvement: SAS Analytics could enhance its user interface to be more intuitive and reduce the complexity of some statistical methods. It would also benefit from a streamlined integration process for quicker deployment and a more flexible pricing model. KNIME might improve in offering more direct enterprise support options, providing better documentation for advanced features, and enhancing its dataset handling for exceptionally large data volumes.

Ease of Deployment and Customer Service: SAS Analytics offers extensive deployment options suitable for large-scale setups, though it may require more time to implement. Its well-established support infrastructure provides reliable customer assistance. KNIME offers a straightforward deployment model, being open-source, with an active community-based support system that enables faster integration of solutions.

Pricing and ROI: SAS Analytics has higher initial costs but justifies these with comprehensive features and potential returns for large-scale projects, albeit the investment can be considerable. KNIME's cost-effective model with less immediate expense and favorable ROI makes it particularly appealing to budget-conscious users who prioritize adaptability in analytics solutions.

To learn more, read our detailed KNIME vs. SAS Analytics Report (Updated: July 2025).

Buyer's Guide

KNIME vs. SAS Analytics

July 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

KNIME

Ranking in Data Mining

1st

Average Rating

8.2

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Data Science Platforms (2nd)

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2025, in the Data Mining category, the mindshare of KNIME is 24.6%, down from 27.0% compared to the previous year. The mindshare of SAS Analytics is 7.3%, down from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Featured Reviews

Laurence Moseley

Emeritus Professor of Health Services Research at University of South Wales

Has a drag-and-drop interface and AI capabilities

It's difficult to pinpoint one single feature because KNIME has so many. For starters, it's very easy to learn. You can get started with just a one-hour video. The drag-and-drop interface makes it user-friendly. For example, if you want to read an Excel file, drag the "read Excel file" node from the repository, configure it by specifying the file location, and run it. This gives you a table with all your data. Next, you can clean the data by handling missing values, selecting specific columns you want to analyze, and then proceeding with your analysis, such as regression or correlation. KNIME has over 4,500 nodes available for download. In addition, KNIME offers various extensions. For instance, the text processing extension allows you to process text data efficiently. It's more powerful than other tools like NVivo and Palantir. KNIME also has AI capabilities. If you're unsure about the next step, the AI assistant can suggest the most frequently used nodes based on your previous work. Another valuable feature is the integration with Python. If you need to perform a task that requires Python, you can simply add a Python node, write the necessary code,

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AltanAtabarut

Solution Consulting, Growth, Analytics at Akinon

Good interactive reports and dashboards but expensive to run

You need to constantly jump from data prep to visualization, then back to data for fixing quality, enriching, and visualizing again. Then you start modeling and need to switch back and forth again. Eventually, you have to democratize the results so that anyone can look and interactively question the underlying insights. For all of these purposes - data to BI or data to AI to BI - it is never a linear one way relationship; it's rather a closed loop for continuous analysis monitoring and sharing. If used this way, SAS Visual analytics can enable continuous improvement and innovation in a corporation.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"It's a huge tool with machine learning features as well."

"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."

"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."

"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."

"Since KNIME is a no-code platform, it is easy to work with."

"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's a very powerful and simple tool to use."

"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."

More KNIME pros

"I use SAS daily to analyze data, produce reports, and other outputs."

"The most valuable feature is the ability to handle large data sets."

"The team immediately resolves the issues."

"All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team."

"It is able to connect to all major platforms, and all the smaller platforms that I have come across."

"The technical support is okay."

"It has improved the level of efficacy and validity of our reports."

"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."

More SAS Analytics pros

Cons

"I've had some problems integrating KNIME with other solutions."

"It could be easier to use."

"The pricing needs improvement."

"In my environment, I need to access a lot of servers with different characteristics and access methods. Some of my servers have to be accessed using proxy which is not supported by KNIME, so I still need to create the middleware to supply the source of my KNIME configurations."

"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."

"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."

"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."

"For graphics, the interface is a little confusing."

More KNIME cons

"The natural language querying and automated preparation of dashboards should be improved."

"I would like to see their interface to R added to either Base SAS or SAS Analytics."

"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."

"They could enhance the AI capabilities of the product."

"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."

"This solution should be made more user-friendly."

"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."

"The installation could also be easier, and the price could be better."

More SAS Analytics cons

Pricing and Cost Advice

"KNIME is an open-source tool, so it's free to use."

"It is expensive to procure the license."

"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."

"With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment."

"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."

"KNIME Business Hub is expensive for small companies."

"For beginners, the free desktop version is very attractive, but the full server version can be more expensive. I have only used the free version and it offers a fair pricing system. I have been promoting it to others without any compensation or request from the company, simply because I am enthusiastic about it. I am not aware of the pricing for the server version, but it seems to be widely used."

"It is free of cost. It is GNU licensed."

More KNIME pricing and cost advice

"I rate the product’s pricing a one out of ten."

"I think that the cost-benefit ratio is okay."

"Setup costs were quite reasonable."

"It is relatively expensive. It is not an easy software to afford."

"Our licensing covers the usage for around 50 data analysts."

"SAS is very expensive."

"Licensing was rather straightforward."

"Prices were comparable with alternative solutions."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Manufacturing Company

10%

Computer Software Company

University

Financial Services Firm

19%

Computer Software Company

11%

Insurance Company

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about KNIME?

Since KNIME is a no-code platform, it is easy to work with.

See all answers

What is your experience regarding pricing and costs for KNIME?

I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.

See all answers

What needs improvement with KNIME?

I have seen the potential to interact with Python, which is currently a bit limited. I am interested in the newer version, 5.4, when it becomes available. The machine learning and profileration asp...

See all answers

What do you like most about SAS Analytics?

I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile app.

See all answers

What needs improvement with SAS Analytics?

SAS Analytics could improve in areas such as handling stress tests and workloads, as well as predicting financial movements, specifically profit and loss movements.

See all answers

What is your primary use case for SAS Analytics?

I use SAS Analytics ( /products/sas-analytics-reviews ) in my work to analyze data, such as selecting credits for traditional securitization. Recently, I used SAS Analytics ( /products/sas-analytic...

See all answers

Comparisons

Altair RapidMiner vs KNIME

Compared 26% of the time

Dataiku vs KNIME

Compared 14% of the time

Microsoft Power BI vs KNIME

Compared 14% of the time

Alteryx vs KNIME

Compared 8% of the time

SAS Enterprise Miner vs KNIME

Compared 1% of the time

More KNIME Competitors

IBM SPSS Statistics vs SAS Analytics

Compared 18% of the time

Oracle Advanced Analytics vs SAS Analytics

Compared 18% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 17% of the time

Weka vs SAS Analytics

Compared 14% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

KNIME

July 2025

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Buyer's Guide

Data Mining

June 2025

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Also Known As

KNIME Analytics Platform

No data available

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.”

Knime

SAS was founded in 1976 and actually began as a project at North Carolina State University to analyze agriculture research. It has since become a global company that is recognized for its innovation in data analytics and business intelligence. SAS is redefining what's possible with data analytics through greater efficiency, strong information value chains, effective collaboration tools, and state-of-the-art visualization software. SAS Analytics is designed for use in a variety of industries including government, manufacturing, higher education, defense & security, banking, automotive, communications, and much more. SAS Analytics is a business intelligence (BI) solution that has the ability to reveal patterns and anomalies in data, identify relationships and different variables, and predict future outcomes. Users of SAS Analytics will benefit from making more sound, better informed business decisions based on company data and market trends. Data mining, data visualization, text analytics, forecasting, statistical analysis, and more are all available through SAS Analytics. Staples, which boasts $27 billion in sales across the globe, has a business philosophy that prioritizes customer loyalty and satisfaction. In order to better engage their customers, Staples utilizes SAS Analytics to plan finely tuned marketing campaigns. Through forecasting and advanced analytics, Staples has been able to rely on fewer contractors, and cut their marketing budget, while improving their customer retention rate.

SAS

Sample Customers

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG

Aegon, Alberta Parks, Amway China, Axel Springer, Bank of America, Belgium Special Tax, CAP Index, CareSource, CBE Group, Cemig, Center for Responsible Lending, CESCE, Ceska sporitelna, Chantecler, Chico's, Chubb Group of Insurance Companies, CIGNA Thailand, City of Wiesbaden, Germany, Confused.com, Creditreform, Des Moines Area Community College, Deutsche Lufthansa, Directorate of Economics and Statistics, DIRECTV, Dow Chemical Company, Dow Chemical Company, Dun & Bradstreet, EDF Energy, Electrabel GDF SUEZ, ERGO Insurance Group, Erste Bank Croatia, Farmers Mutual Group, Finnair, Florida Department of Corrections, Geneia, Generali Hellas, Genting Malaysia Berhad, Grameenphone, Grandi Salumifici Italiani, HealthPartners, Highmark, Hong Kong Efficiency Unit, HP, Hyundai Securities, Illinois Department of Healthcare and Family ServicesInc Research, ING-DiBa, Institut Pertanian Bogor, InterContinental Hotels Group (IHG), IOM, Kelley Blue Book, Lenovo, Lillebaelt Hospital, Los Angeles County, Maspex Wadowice Group, National Bank of Greece, New Zealand Ministry of Health, New Zealand Ministry of Social Development, Nippon Paper, NMIMS, North Carolina Department of Transportation, North Carolina Office of Information Technology Services, Northern Virginia Electric Cooperative (NOVEC), Oberweis Dairy, ODEC, Ohio Mutual Insurance Group, Oklahoma State University, OneBeacon, Orange Business Services, Orange County Child Support Services, Organic, Orlando Magic, OTP Bank, Plano Independent School District, Project Odyssey, Royal Society for the Protection of Birds, RSA Canada, SCAD, Scotiabank, Singapore National Library Board, Sobeys Inc., SRA International, Staples, Statistics Estonia, Swisscom, SymphonyIRI Group, Telecom Italia, Telef‹nica O2, Town of Cary, Transitions Optical, TrueCar, Turkcell Superonline, UniCredit Bank Serbia, University of Alabama, University of Missouri, USDA National Agricultural Statistics Service

Buyer's Guide

KNIME vs. SAS Analytics

July 2025

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Find out what your peers are saying about KNIME vs. SAS Analytics and other solutions. Updated: July 2025.

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