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 66 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

"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."

"The solution allows for sharing model designs and model operations with other data analysts."

"The tool's analytic capabilities are good."

"We are able to automate several functions which were done manually, and I can integrate several data sets quickly and easily to support analytics."

"I am very happy with the product and it would be hard to find something better in the market."

"There are a lot of connectors available in KNIME."

"I've tried to utilize KNIME to the fullest extent possible to replace Excel."

"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."

More KNIME Business Hub pros

"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."

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

"It has facilitated timely analysis results with quality work, meaningful output, and consistent data use."

"It has also been around for an extremely long time, has a strong history, and good market penetration."

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

"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."

"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."

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

More SAS Analytics pros

Cons

"KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile."

"It could be easier to use."

"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."

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

"I feel the query performance is slower than my old code."

"It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."

"The diversity of native algorithms could be improved."

"I wish there were more video training resources for KNIME. The current videos are very short, and most learning is text-based. Longer training sessions would be helpful, especially for complex flowchart use cases. Webinars focusing on starting projects and analyzing data would also be beneficial."

More KNIME Business Hub cons

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

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

"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 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. It needs a better visual output to explain logic to senior executives."

"It is relatively expensive."

"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."

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

More SAS Analytics cons

Pricing and Cost Advice

"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."

"KNIME is a cheap product. I currently use KNIME's open-source version."

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

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

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

"At this time, I am using the free version of Knime."

"This is a free open-source solution."

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

More KNIME Business Hub pricing and cost advice

"Prices were comparable with alternative solutions."

"SAS is very expensive."

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

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

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

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

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

"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

11%

Manufacturing Company

University

Outsourcing Company

Financial Services Firm

25%

Outsourcing Company

14%

University

11%

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	22
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?

KNIME Business Hub could be improved by making the user experience more intuitive, especially for users who are new to data analytics. More guided features and documentation would be beneficial.

See all answers

What is your primary use case for KNIME?

I automated the processing of paper-based data by digitalizing scanned documents and creating a KNIME Business Hub workflow that transforms the data into an analysis-ready format, reducing a manual...

See all answers

What advice do you have for others considering KNIME?

My advice to others looking into using KNIME Business Hub would be to start experimenting. Do not be afraid of KNIME Business Hub, even if you do not have a strong programming background. Start wit...

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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Product Reports

Buyer's Guide

KNIME Business Hub

October 2026

Download KNIME Business Hub product report

Buyer's Guide

SAS Analytics

September 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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