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Anaconda Business vs Cloudera Data Science Workbench 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

Anaconda Business
Ranking in Data Science Platforms
7th
Average Rating
8.2
Reviews Sentiment
6.6
Number of Reviews
31
Ranking in other categories
No ranking in other categories
Cloudera Data Science Workb...
Ranking in Data Science Platforms
24th
Average Rating
7.0
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2026, in the Data Science Platforms category, the mindshare of Anaconda Business is 2.1%, down from 2.1% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.6%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Anaconda Business2.1%
Cloudera Data Science Workbench1.6%
Other96.3%
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.
Ismail Peer - PeerSpot reviewer
Program Management Lead Advisor at Unionbank Philippines
Useful for data science modeling but improvement is needed in MLOps and pricing
If you don't configure CDSW well, then it might be not useful for you. Deploying the tool can vary in complexity, but most of the time, it's relatively simple and straightforward. Triggering a job from data to production is easy, as the platform automates the deployment process. However, ensuring optimal resource allocation is essential for smooth operations.

Quotes from Members

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

Pros

"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"Using Anaconda Business, I have seen huge time-saving due to the automation of monitoring and deployment, which has led to significant improvements."
"With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place, and the platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages."
"Previously, we were using RStudio, PyCharm for data science domain, but with this software, we've got a perfect platform to teach data science."
"The biggest positive impact has been the consistency it brings, since everyone can use clean, isolated environments, we run into far fewer package conflicts or situations where something works on one system but not another."
"This is a great tool to work with, even if you are starting your career in analytics or another stream like data engineering or data science."
"The solution's most valuable aspects include the repositories, the way we log, the way we install that repository management, and how we can easily integrate the solution with Jupyter Notebook."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"The Cloudera Data Science Workbench is customizable and easy to use."
 

Cons

"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"The pricing should be a little lower for a single person to use, as it might be affordable for an organization, but for my single use, it is difficult."
"One feature that I would like to see is being able to use a different language in a different cell, which would allow me to mix R and Python together."
"The setup was quite complex."
"Anaconda Business could be improved because currently, if a package is not added to the curated repository, our teams may wait hours or days for security license validation."
"One thing that hurts the product is that the company is not doing more to advertise it as a solution and make it more well known that I have seen."
"Anaconda consumes a significant amount of processing memory when working on it."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"We found this solution a little bit difficult to scale."
"The tool's MLOps is not good. It's pricing also needs to improve."
 

Pricing and Cost Advice

"The product is open-source and free to use."
"The tool is open-source."
"My company uses the free version of the tool. There is also a paid version of the tool available."
"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."
"The licensing costs for Anaconda are reasonable."
"The product is expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
University
10%
Manufacturing Company
7%
Construction Company
7%
Financial Services Firm
30%
Computer Software Company
8%
Wholesaler/Distributor
7%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise2
Large Enterprise20
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?
Anaconda Business could be improved by being more integrated with new CLI tools like Cloud Code or Codex.
What is your primary use case for Anaconda?
I use Anaconda Business day-to-day, with the main tool being Jupyter Notebook, which I have on my computer for cleaning and extracting data. I extract data from Excel using Anaconda Business and cl...
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Also Known As

No data available
CDSW
 

Overview

 

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
IQVIA, Rush University Medical Center, Western Union
Find out what your peers are saying about Anaconda Business vs. Cloudera Data Science Workbench and other solutions. Updated: June 2026.
904,973 professionals have used our research since 2012.