Try our new research platform with insights from 80,000+ expert users

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
6.8
Number of Reviews
29
Ranking in other categories
No ranking in other categories
Cloudera Data Science Workb...
Ranking in Data Science Platforms
23rd
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 February 2026, in the Data Science Platforms category, the mindshare of Anaconda Business is 2.4%, up from 2.1% compared to the previous year. The mindshare of Cloudera Data Science Workbench is 1.7%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Anaconda Business2.4%
Cloudera Data Science Workbench1.7%
Other95.9%
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 notebook feature is an improvement over RStudio."
"Anaconda Business has positively impacted my organization because, when discussing the security point of view, it's exceptional; when comparing it to other solutions, Anaconda Business is superior."
"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."
"Anaconda Business provides a 60 to 70% faster environment setup, zero security incidents, lower compliance costs, and better productivity."
"It's interesting. It's user friendly. That's what makes it outstanding among the others. It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science."
"The documentation is excellent and the solution has a very large and active community that supports it."
"Specific examples of improvements since using Anaconda Business include faster environment setup, where teams can instantly create and share standardized environments, eliminating dependency hell and allowing focus on analysis rather than administrative work."
"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."
"The Cloudera Data Science Workbench is customizable and easy to use."
"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."
 

Cons

"My suggestion for improvement is that they should enhance the security point of view; it's good, but it needs some more advanced features."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"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."
"Anaconda can't handle heavy workloads."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"Sometimes the environment creation or package installation feels a bit slow, especially with bigger libraries."
"Interaction and speed can be improved."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"The tool's MLOps is not good. It's pricing also needs to improve."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
 

Pricing and Cost Advice

"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 tool is open-source."
"The product is open-source and free to use."
"The product is expensive."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
882,744 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
16%
University
11%
Manufacturing Company
8%
Computer Software Company
7%
Financial Services Firm
35%
Manufacturing Company
9%
Healthcare Company
7%
Computer Software Company
5%
 

Company Size

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

Questions from the Community

What do you like most about Anaconda?
The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.
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 installation process and efficiency to avoid system freezing.
What do you like most about Cloudera Data Science Workbench?
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...
What needs improvement with Cloudera Data Science Workbench?
The tool's MLOps is not good. It's pricing also needs to improve.
What is your primary use case for Cloudera Data Science Workbench?
We have different use cases. Our banking use case uses machine learning to identify customer life events and recommend the best-suited card products. These machine-learning models are deployed in o...
 

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: February 2026.
882,744 professionals have used our research since 2012.