KNIME Business Hub vs SAS Analytics comparison

Why PeerSpot?

Knime and SAS are both solutions in the Data Mining category. Knime is ranked #1 with an average rating of 8.5, while SAS is ranked #5 with an average rating of 8.5. Knime holds a 10.6% mindshare in DM, compared to SAS’s 8.2% mindshare. Additionally, 94% of Knime users are willing to recommend the solution, compared to 95% of SAS users who would recommend it.

KNIME Business Hub

Read 65 KNIME Business Hub reviews

9,750 Views
2,048 Comparison Views

94% willing to recommend

SAS Analytics

Read 13 SAS Analytics reviews

1,791 Views
1,773 Comparison Views

95% willing to recommend

KNIME Business Hub

SAS Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on Feb 8, 2026

SAS Analytics and KNIME Business Hub are both prominent in the data analytics space, each catering to different user needs. KNIME Business Hub proves advantageous due to its flexibility and integration capabilities, ideal for innovative data projects.

Features: KNIME Business Hub provides easy ETL operations, a rich algorithm set, and integration with other languages like R, Python, and Java. Its open-source nature offers cost-effective and expansive data processing. SAS Analytics features comprehensive analytical tools, advanced statistical analysis, predictive modeling, and strong integration with major platforms. Its ease of use with coding languages like SQL makes it accessible for users familiar with such environments.

Room for Improvement: KNIME could enhance its interface for larger-scale enterprise deployment, improve real-time data processing capabilities, and expand its community-driven resources. SAS Analytics might focus on simplifying its deployment process, offer more robust support for new users, and reduce software complexity to cater equally well to non-technical users.

Ease of Deployment and Customer Service: KNIME Business Hub facilitates adaptable deployment models, allowing seamless cloud or on-premise integration supported by a strong user community. SAS Analytics requires a more specialized deployment environment but offers extensive professional support services, emphasizing dedicated assistance for customers.

Pricing and ROI: KNIME Business Hub is attractive due to its low initial investment costs and high long-term ROI, favored by those seeking open-source advantages. SAS Analytics involves higher upfront investment, justified by its powerful analytics and substantial data-driven insights that can lead to significant ROI if utilized effectively.

To learn more, read our detailed KNIME Business Hub vs. SAS Analytics Report (Updated: September 2026).

Buyer's Guide

KNIME Business Hub vs. SAS Analytics

September 2026

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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 Business Hub

Ranking in Data Mining

1st

Average Rating

8.2

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Science Platforms (5th)

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.2

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2026, in the Data Mining category, the mindshare of KNIME Business Hub is 10.6%, down from 18.4% compared to the previous year. The mindshare of SAS Analytics is 8.2%, up from 6.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining Mindshare Distribution
Product	Mindshare (%)
KNIME Business Hub	10.6%
SAS Analytics	8.2%
Other	81.2%

Data Mining

Featured Reviews

Filippo Elmino

Data Analyst at Politecnico di Milano

Automation has transformed payroll reporting and empowers nontechnical teams to run data workflows

KNIME Business Hub could be improved by increasing integration between KNIME and other tools, such as where companies store data and data visualization tools, making it easier to integrate with these tools and faster to create dashboard updates and quick data extraction through KNIME. An ETL process must communicate with both data sources and the data visualization layer. The integration needs to be more robust, and the nodes that act as connectors to these sources and tools need to be more robust, as the flow often broke when the problem was just a connection issue. This should be improved and perhaps expanded. Another problem was that KNIME could not integrate with all tools. Expanding the possibilities of creating reports and connecting to data visualization tools, especially on the data visualization side, would be useful. The output of an ETL process or ETL flow is visualization through a dashboard or report, so more downstream integration in the process would be needed. Regarding improvements needed in KNIME Business Hub, there may be a hierarchy of users and certain applications created. On the security side of accessing company data, I do not know whether this is already sufficiently considered by KNIME or not. I hope so, because certain data are sensitive and need to be handled with care. The fact that KNIME is enabled to access such data means you also need to ensure that authorizations and data processing policies are respected. Because some company data are sensitive, the fact that KNIME reads them also requires guaranteeing that a policy is respected on the other side. I hope this has already been considered by KNIME Business Hub; I am not aware, but if it has not, this could be an aspect to consider: privacy and the protection of company data when they are read by a system that is not company-owned but still must read them with all proper requirements and safeguards.

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Sanjay Charitesh Makam

Student at Rochester Institute of Technology

Data management has become faster and clearer but integration and large data handling still need work

SAS Analytics needs to improve for entry-level people in my college because buying licenses is somewhat costly for small businesses. SAS Analytics is also somewhat complex for students who are entering the data field. Additionally, SAS Analytics is not good at integration with other environments, so it should improve on that, and some syntaxes are not good. SAS Analytics has an older architecture in some areas, so it should enhance the UX side and performance in some aspects. SAS Analytics documentation should improve to be clearer for students who are currently using or trying to use SAS Analytics, so the documentation should be simplified. Customer service is pretty good as of now, as they respond in two to four hours on business days, but faster response times may solve many problems and attract more users. I rate SAS Analytics seven or eight out of ten. SAS Analytics should improve in massive data handling, as I mentioned earlier. SAS Analytics struggles when it handles massive data, and it should also get top-tier support. The support should improve from two to four hours down to one hour or even thirty minutes. SAS Analytics should also offer more low-code options for those who do not know how to code or to save more time, and they should consider reducing their pricing. Currently, SAS Analytics has limited flexibility and very limited integration, so improvements in those areas are necessary. SAS Analytics student version does not handle long or lengthy data well right now, so it should improve on that point. As I have mentioned, it struggles with larger data sets, but for current small or medium data sets, it is very good. Customer support should improve to fifteen to thirty minutes or immediate live agents during business hours. The two to four hours wait can sometimes take more than one day, and that does not make sense. We have to stop all our work until they reply if we encounter critical problems, so they should improve for certain.

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 provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."

"I believe the main benefits I receive from KNIME Business Hub are automation, because when I work through the workflow one time, I can reuse it later on, saving considerable time for many tasks."

"The solution allows one to do many things, including data preparation, and I was able to apply basic algorithms through just dragging and dropping, in contrast to Python and other solutions, which involve much coding."

"We have been using these features extensively and we find them to be very valuable in achieving what we hoped to achieve with the tool."

"This solution is easy to use and it can be used to create any kind of model."

"KNIME is very easy to handle and use. Anyone can use it, and it's easy to learn."

"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."

"If you like data analysis, KNIME is the best option; it's free and easy to set up."

More KNIME Business Hub pros

"This solution has helped us materially grow multiple business categories."

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

"SAS Analytics is a very versatile and comfortable tool and it is powerful because I can work with data from many millions of records, big data with SAS Analytics in a short time versus other software."

"I use it to replicate our entire financial system to verify/duplicate calculations."

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

"It has improved the level of efficacy and validity of our reports, and this has also extended to the area of customer service and relations."

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

"SAS Business Intelligence is well-suited for our large corporation, as we have demand for scalable and reliable insights into information which is housed in our large systems."

More SAS Analytics pros

Cons

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

"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."

"We do not have much documentation in Portuguese."

"The ability to handle large amounts of data and performance in processing need to be improved."

"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."

"KNIME needs to provide more documentation and training materials, including webinars or online seminars."

"In the previous versions, I had some issues when reading large Excel files due to memory usage."

"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."

More KNIME Business Hub cons

"With SAS Analytics, I find that the graphs are very poor, and since I use Power BI, I think SAS Analytics needs to enhance the visualization options to do better visualizations."

"Support at universities used to be limited, but I hear this is changing."

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

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

"SAS is very expensive. The challenge with them is that you have to pay for a license with every module you buy."

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

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

"SAS Analytics struggles when it handles massive data, and it should also get top-tier support."

More SAS Analytics cons

Pricing and Cost Advice

"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."

"The price of KNIME is quite reasonable and the designer tool can be used free of charge."

"The price for Knime is okay."

"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 desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."

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

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

More KNIME Business Hub pricing and cost advice

"SAS is very expensive."

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

"The cost for SAS Business Intelligence can prove to be a little prohibitive."

"Prices were comparable with alternative solutions."

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

"Licensing was rather straightforward."

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

"Setup costs were quite reasonable."

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

10%

Manufacturing Company

University

Outsourcing Company

Financial Services Firm

23%

Outsourcing Company

14%

University

12%

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	21
Midsize Enterprise	16
Large Enterprise	35

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	11

Questions from the Community

What needs improvement with KNIME?

See all answers

What is your primary use case for KNIME?

I used KNIME Business Hub in my previous role for approximately six months, from April to September 2025. The primary use case for KNIME Business Hub was creating an ETL flow for the HR team that g...

See all answers

What advice do you have for others considering KNIME?

Regarding concrete examples of metrics or results obtained with KNIME Business Hub, we definitely saved a lot in terms of time and productivity. The work was also much more fluid and activities wer...

See all answers

What needs improvement with SAS Analytics?

With SAS Analytics, I find that the graphs are very poor, and since I use Power BI, I think SAS Analytics needs to enhance the visualization options to do better visualizations. Many other software...

See all answers

What is your primary use case for SAS Analytics?

I work with SAS Analytics solutions, specifically with SAS Data Mining, because I extract information from the core system of the bank via ODBC connections and use SAS Base on the servers. I am the...

See all answers

What is your experience regarding pricing and costs for SAS Analytics?

As a student, I do not pay anything for pricing; my college gives me credentials, and SAS Analytics is free for students, so the licensing is also free. Thus, SAS Analytics for students is very good.

See all answers

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Compared 7% of the time

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Compared 2% of the time

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Compared 12% of the time

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Compared 11% of the time

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Compared 9% of the time

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Product Reports

Buyer's Guide

KNIME Business Hub

October 2026

Download KNIME Business Hub product report

Buyer's Guide

SAS Analytics

October 2026

Download SAS Analytics product report

Also Known As

KNIME Analytics Platform

No data available

Overview

KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.

KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.

What are the most important features of KNIME Business Hub?

No-Code Interface: Simplifies data preparation without coding expertise.
Node Library: Supports diverse data tasks, including ETL and machine learning.
Python and R Integration: Seamlessly connects with popular programming languages.
Automation Capabilities: Enhances workflow productivity.
Visual Workflow Tools: Offers efficient data handling with visual aids.

What benefits and ROI can users expect from KNIME Business Hub?

Increased Productivity: Streamlined data tasks reduce development time.
Community Support: Access to extensive resources and user assistance.
Cost-Effective: Robust performance even on standard hardware.
Accessible Learning Curve: Simplicity allows easy access for educational and professional use.
Enhanced Prototyping: Ideal for decision model testing.

KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.

Knime

SAS Analytics offers a powerful suite of tools for statistical analysis, predictive analytics, and data handling, making it ideal for industries requiring robust data-driven decisions. Its extensive capabilities cater to professionals familiar with SQL and demand forecasting needs across sectors.

With a strong presence in analytics, SAS Analytics provides a seamless experience for data preparation, exploration, and reporting. Users benefit from its ability to handle large data sets, generate interactive reports, and integrate with multiple platforms. Despite its high costs and need for improved visualization and natural language querying, SAS Analytics remains a favored choice for those requiring comprehensive statistical modeling and risk analytics. Enhancing self-service analytics and accelerating support response times are areas of needed improvement. Companies use it extensively for business intelligence and demand forecasting, particularly in sectors like banking and financial services.

What are the key features of SAS Analytics?

Interactive Reports: Embeds intuitive and engaging reports.
Extensive Analytics Functions: Offers a wide range of analytics capabilities.
SQL Compatibility: Streamlines use for SQL-proficient users.
Predictive Analytics: Enhances analysis with SAS E-Miner.
Automation: Utilizes macros for automated tasks.
Large Data Handling: Manages extensive data effectively.

What benefits can users look for in reviews?

Increased Productivity: Saves time with automation and efficient data processing.
Enhanced Efficiency: Direct data source connections streamline workflows.
Versatility: Adapts to diverse analytical and reporting requirements.
Comprehensive Resources: Provides extensive help and support materials.

SAS Analytics is widely implemented in industries for tasks like national auto insurance pricing, financial replication, and marketing analytics. Teams in banking and financial services apply it for quantitative analyses, risk assessments, and generating detailed operational reports, demonstrating its adaptability and strength in handling complex data scenarios.

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 Business Hub vs. SAS Analytics

September 2026

Free Report: KNIME Business Hub vs. SAS Analytics

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