KNIME vs SAS Analytics comparison

KNIME

Read 51 KNIME reviews

2,818 Views
1,975 Comparison Views

93% willing to recommend

SAS Analytics

Read 11 SAS Analytics reviews

900 Views
706 Comparison Views

94% willing to recommend

KNIME

SAS Analytics

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between KNIME and SAS Analytics based on real PeerSpot user reviews.

Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed KNIME vs. SAS Analytics Report (Updated: May 2024).

Buyer's Guide

KNIME vs. SAS Analytics

May 2024

Download the complete report

Helped 787,061 peers since 2012

Categories and Ranking

KNIME

Ranking in Data Mining

1st

Average Rating

8.2

Number of Reviews

Ranking in other categories

Data Science Platforms (4th)

SAS Analytics

Ranking in Data Mining

5th

Average Rating

9.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Market share comparison

As of June 2024, in the Data Mining category, the market share of KNIME is 19.7% and it decreased by 28.7% compared to the previous year. The market share of SAS Analytics is 4.6% and it decreased by 65.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

Unique Categories:

Data Science Platforms

11.8%

No other categories found

Featured Reviews

Laurence-Moseley

Professor of Health Services Research (now Emeritus) at a university with 1,001-5,000 employees

Jan 10, 2023

Simple to learn, useful no code platform, and quick and efficient

There are many valuable features in KNIME. One of the most useful aspects is that it can read a wide variety of data file types. Additionally, the ability to manipulate data, such as deleting rows or columns, is very helpful. I also use many of the nodes for analyzing data, such as doing frequencies and cross tabs. I have used it for machine learning tasks, like decision trees and random forests. It also has neural network capabilities, but I am not an expert in that area, so I cannot comment on it. It's a very powerful and simple tool to use. KNIME has met all of my needs so far. It has excellent data visualization capabilities. Additionally, it has a text analysis package, which I haven't used. However, I am satisfied with the features currently available and it has a strong support community.

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Tanin U

Assistant Vice President at AEON Thana Sinsap

Jan 25, 2024

Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks

SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency. While our current setup operates smoothly, certain partners still rely on another platform, specifically the virtualization dashboard. I believe it's a significant improvement compared to the traditional approach I've been using for the past ten years. Previously, when management had inquiries, they would create documents or memos, and IT would then track down the data, interpret it, and provide feedback. This process involved explaining the data structure, database, and definitions in the data warehouse. Now, with SAS Analytics, the workflow is much smoother and faster. IT is more streamlined, allowing for quicker access to data, and managers can directly access and utilize the sales reports.

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Quotes from Members

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

Pros

"The product is open-source and therefore free to use."

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

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

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

"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."

"This solution is easy to use and especially good at data preparation and wrapping."

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

"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."

More KNIME pros

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

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

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

"It has facilitated timely analysis results with quality work and meaningful output."

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

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

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

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

More SAS Analytics pros

Cons

"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."

"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."

"The license is quite expensive for us."

"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."

"The data visualization part is the area most in need of improvement."

"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."

"The predefined workflows could use a bit of improvement."

More KNIME cons

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

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

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

"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."

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

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

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

"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."

More SAS Analytics cons

Pricing and Cost Advice

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

"Scaling to the on-premises version requires a licensing fee per user that is a bit expensive in comparison to R, Python, and SAS."

"The price for Knime is okay."

"While there are certain limitations in functionality, you can still utilize it efficiently free of charge."

"KNIME is a cost-effective solution because it’s free of cost."

"We're using the free academic license just locally. I went for KNIME because they have a free academic license."

"It is expensive to procure the license."

"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."

More KNIME pricing and cost advice

"Setup costs were quite reasonable."

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

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

"The pricing tends to be higher, and there are additional expenses involved."

"Licensing was rather straightforward."

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

"SAS is very expensive."

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

More SAS Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Manufacturing Company

12%

Financial Services Firm

11%

Computer Software Company

Educational Organization

Financial Services Firm

12%

University

11%

Educational Organization

10%

Computer Software Company

10%

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?

We're using the free academic license just locally. I went for KNIME because they have a free academic license. And to be honest, I never bothered to check the prices.

See all answers

What needs improvement with KNIME?

KNIME is not good at visualization. I would like to see NLQ (Natural language query) and automated visualizations added to KNIME.

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?

The natural language querying and automated preparation of dashboards should be improved. The cost and accessibility should be improved. For a $900 USD/user/annual license you have to set up a $12,...

See all answers

What is your primary use case for SAS Analytics?

This is an application I use for data prep, data exploration, BI reporting, and some basic automated analytics.

See all answers

Comparisons

RapidMiner vs KNIME

Compared 26% of the time

Microsoft Power BI vs KNIME

Compared 20% of the time

Alteryx vs KNIME

Compared 13% of the time

Dataiku vs KNIME

Compared 8% of the time

Tableau vs KNIME

Compared 1% of the time

More KNIME Competitors

IBM SPSS Statistics vs SAS Analytics

Compared 22% of the time

Weka vs SAS Analytics

Compared 16% of the time

SAS Enterprise Miner vs SAS Analytics

Compared 8% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 8% of the time

More SAS Analytics Competitors

Product Reports

Buyer's Guide

KNIME

June 2024

Download KNIME product report

Buyer's Guide

Data Mining

June 2024

Download SAS Analytics product report

Also Known As

KNIME Analytics Platform

No data available

Learn More

Knime

SAS

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.”

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.

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

May 2024

Free Report: KNIME vs. SAS Analytics

Find out what your peers are saying about KNIME vs. SAS Analytics and other solutions. Updated: May 2024.

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