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Anaconda Business vs KNIME Business Hub vs Oracle DataScience.com Platform comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Mindshare comparison

As of May 2026, in the Data Science Platforms category, the mindshare of Anaconda Business is 2.2%, up from 2.1% compared to the previous year. The mindshare of KNIME Business Hub is 5.6%, down from 11.9% compared to the previous year. The mindshare of Oracle DataScience.com Platform is 0.6%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
KNIME Business Hub5.6%
Anaconda Business2.2%
Oracle DataScience.com Platform0.6%
Other91.6%
Data Science Platforms
 

Featured Reviews

reviewer2775498 - PeerSpot reviewer
tester at a tech vendor with 10,001+ employees
Isolate environments and switch package versions efficiently for smoother testing workflows
Overall, it works well, but there are a few things that could be better. Sometimes the environment creation or package installation feels a bit slow, especially with bigger libraries. Another thing I would appreciate is a cleaner, more intuitive interface for managing environments. It works, but a smoother UI could make the workflow faster. It would also be nice to have clearer error messages when something fails, so it is easier to understand what went wrong without digging too much. The documentation could be a bit clearer, especially for troubleshooting specific errors or setup issues. Sometimes I need to search extensively to find the exact steps. Also, having quicker or more detailed support responses would help when something unexpected comes up. These are not major problems, but improving them would definitely make the overall experience smoother. One small improvement I would add is smoother integration with IDEs. It works fine right now, but having even tighter or more automated syncing with tools such as VS Code or PyCharm would make the workflow faster. Perhaps also a few more built-in examples or quick-start guides for common setups would be helpful. Nothing major, just things that would make the experience even more user-friendly.
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.
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
University
12%
Manufacturing Company
7%
Computer Software Company
7%
Financial Services Firm
12%
Manufacturing Company
9%
University
8%
Educational Organization
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise2
Large Enterprise19
By reviewers
Company SizeCount
Small Business21
Midsize Enterprise16
Large Enterprise32
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Anaconda?
My experience with pricing, setup cost, and licensing is that it is a little costly, but it is useful.
What needs improvement with Anaconda?
I believe Anaconda Business can be improved in terms of performance and speed, particularly regarding the installatio...
What is your primary use case for Anaconda?
I have been using Anaconda Business for a couple of years since 2022 when I started data analysis, utilizing it for P...
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...
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 util...
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Also Known As

No data available
KNIME Analytics Platform
Oracle Data Science Platform, DataScience.com Platform, DataScience, DataScience.com
 

Overview

 

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Sonos, Just Fab, Tradesy, Belkin, DogVacay, Scopely, Topix, Home Chef, Pluto
Find out what your peers are saying about Databricks, Dataiku, Knime and others in Data Science Platforms. Updated: May 2026.
895,990 professionals have used our research since 2012.