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FICO Decision Management vs KNIME Business Hub comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 8, 2026

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

FICO Decision Management
Ranking in Data Science Platforms
27th
Average Rating
9.0
Reviews Sentiment
6.7
Number of Reviews
4
Ranking in other categories
Decision Management Tools (2nd)
KNIME Business Hub
Ranking in Data Science Platforms
3rd
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
63
Ranking in other categories
Data Mining (1st)
 

Mindshare comparison

As of June 2026, in the Data Science Platforms category, the mindshare of FICO Decision Management is 1.5%, up from 0.4% compared to the previous year. The mindshare of KNIME Business Hub is 5.1%, down from 12.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
KNIME Business Hub5.1%
FICO Decision Management1.5%
Other93.4%
Data Science Platforms
 

Featured Reviews

it_user147981 - PeerSpot reviewer
Project Manager at a financial services firm with 501-1,000 employees
I would recommend buying this product for loan origination purposes
FICO OM is very flexible in terms of development, with rapid application development options Streamlined loan origination processes. Credit products. Two years. No. No. Below average. Straightforward. Flexible. Yes, we did. I would recommend buying this product for loan origination…
NataliaRaffo - PeerSpot reviewer
Co Founder & Chief Data Officer Cdo at NTT DATA
Workflow automation has accelerated advanced analytics and machine learning delivery
Sometimes it is a little bit difficult to use some nodes when we have many large-scale data, for example, CSV files with a large amount of data. It is sometimes difficult to try to import the data in KNIME Business Hub nodes because I think that some features that are in the CSV in text, for example, large text, is difficult for KNIME Business Hub to import these fields. I don't know why, but it is very difficult. We need to try to use different nodes for importing the data, such as File Reader and CSV Reader. However, I think that it is always the features that have much text, it is difficult for KNIME Business Hub to understand and import this information. I don't know why, or maybe I don't know if we don't know what the better option is to configure the node to import all the CSV or the data set. However, we have always had this problem. In some nodes, sometimes it is the same because sometimes, for example, I have a CSV and in my CSV, I have a feature that is, for example, a date. When I import this data set in the File Reader node, I have problems with this field because it is a date, but the problem is that it imports it as text, for example. We try to use their nodes that convert text to date, but sometimes it is difficult, and it is not immediate to transform the text into a date. So we needed to convert the text into a date in the CSV, and then import it again in the KNIME Business Hub node and try to have a good read of this field. I know that KNIME Business Hub has some nodes to convert text to date and others, but sometimes it is difficult to use these nodes. I don't know why. Maybe it needs a specific format for the date and we need to transform our feature in this option. So sometimes it is a large process to convert these features. However, sometimes we need to investigate and search for other nodes, and try with other nodes to import these cases.

Quotes from Members

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

Pros

"FICO OM is very flexible in terms of development, with rapid application development options."
"It's a very powerful and simple tool to use."
"The most useful features are the readily available extensions that speed up the work."
"I use it personally for my purposes and for the company; I use it for internal data science with very good results."
"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."
"The most valuable features of KNIME are its ability to convert your sub-workflow into a node. For example, the workflow has many individual native nodes that can be converted into a single node. This representation has simplified my workflow to a great extent. I can present my workflow in a very compact way."
"This is a very handy tool and I use it quite interactively."
"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."
"It is a free open-source tool that performs very similarly to other expensive tools."
 

Cons

"Customer service is below average."
"There should be better documentation and the steps should be easier."
"The pricing needs improvement."
"For graphics, the interface is a little confusing. So, this is a point that could be improved."
"If they had a more structured training model it would be very helpful."
"I feel the query performance is slower than my old code."
"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."
"Sometimes, we needed more space to handle larger operations, especially since our machines had limited space and memory due to Kubernetes clusters."
"The user interface could be a bit better."
 

Pricing and Cost Advice

Information not available
"KNIME is free and open source."
"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 an open-source tool, so it's free to use."
"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."
"KNIME Business Hub is expensive for small companies."
"They have different versions, but I am using the open-source one."
"It is free of cost. It is GNU licensed."
"Scaling to the on-premises version requires a licensing fee per user that is a bit expensive in comparison to R, Python, and SAS."
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Top Industries

By visitors reading reviews
Financial Services Firm
28%
Comms Service Provider
8%
Manufacturing Company
7%
Outsourcing Company
7%
Financial Services Firm
12%
Manufacturing Company
9%
University
8%
Educational Organization
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business21
Midsize Enterprise16
Large Enterprise32
 

Questions from the Community

Ask a question
Earn 20 points
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.
What needs improvement with KNIME?
I would describe KNIME Decision Hub as somewhat helpful in making data-driven decisions more efficient. It could have been a scalable decisioning as a service at the back end, but it's not working ...
What is your primary use case for KNIME?
I mainly use KNIME Business Hub currently for data ETLs and then it meets with predictive analytics. Sometimes I utilize it for forecasting, but mostly it's predictive analytics. I have utilized bo...
 

Also Known As

No data available
KNIME Analytics Platform
 

Overview

 

Sample Customers

Aiful, Raiffeisen Bank International AG
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about Databricks, Dataiku, Knime and others in Data Science Platforms. Updated: May 2026.
902,270 professionals have used our research since 2012.