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Anaconda vs SAS Visual Analytics 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:
 

Categories and Ranking

Anaconda
Average Rating
8.2
Reviews Sentiment
7.4
Number of Reviews
19
Ranking in other categories
Data Science Platforms (11th)
SAS Visual Analytics
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
40
Ranking in other categories
Data Visualization (6th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Anaconda is designed for Data Science Platforms and holds a mindshare of 2.1%, up 2.1% compared to last year.
SAS Visual Analytics, on the other hand, focuses on Data Visualization, holds 4.0% mindshare, down 6.0% since last year.
Data Science Platforms
Data Visualization
 

Featured Reviews

Rohan Sharma - PeerSpot reviewer
Provides all the frameworks and makes it easy to create environments for multiple projects
The best thing is that it provides all the frameworks and makes it easy to create environments for multiple projects using Anaconda. It is easy for a beginner to learn to use Anaconda. Comparatively, it is easier than using virtual environments or other environments because of the Conda environment. However, there are many things in Anaconda that people need to be aware of, so it can be challenging.
Danna Nemeth - PeerSpot reviewer
Provides ease of use and has advanced data visualization capabilities
The initial setup can be complex and depends on the specific environment and licensing. It typically requires some time and effort to configure properly. It can be deployed as a SaaS solution or on-premises. It typically requires an installer and someone knowledgeable in business analytics and data management. Generally, it does not require extensive maintenance, though occasional upkeep might be necessary.

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."
"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. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages."
"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."
"I can use Anaconda for non-heavy tasks."
"The documentation is excellent and the solution has a very large and active community that supports it."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"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 most valuable feature is the set of libraries that are used to support the functionality that we require."
"It's a stable, reliable product."
"The technical support services are good."
"Great for handling complex data models."
"It's relatively simple to create basic dashboards and reports."
"It integrates well with SAS, making it simple and quick for developers."
"We've found the product to be stable and reliable."
"Quick deployment to dashboards and analytics features (using SAS Visual Statistics and Enterprise Guide). Easy to create a simple forecast and discover business insights using segmentation tools."
"Simplifies report designs and quickly displays tables and graphs."
 

Cons

"The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"Anaconda should be optimized for RAM consumption."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"Anaconda can't handle heavy workloads."
"It crashes once in a while. In case of a reboot or something unexpected, the unseen code part will get diminished, and it relatively takes longer than other applications when a reboot is happening. They can improve in these areas. They can also bring some database software. They have software for analytics and virtualization. However, they don't have any software for the database."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"In Brazil, there are few documents, courses, and other resources for studying and implementing the tool."
"It is not as mature as competitors such as Tableau and QlikView."
"The solution is a little weak at the front end."
"Colours used on report objects"
"SAS Visual Analytics could improve by making it more accessible for users outside the organization."
"The licensing ends up being more expensive than other options."
"The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive."
"A bit more flexibility in the temperatization will be helpful."
 

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."
"It was licensed for corporate use, and its licensing was on a yearly basis."
"I work with the tool's free version...The tool's corporate version is very expensive and requires a monthly hire."
"Licensing is simple."
"$10,000 per annum for an enterprise license."
"The cost of the solution can be expensive. There is an additional cost for users."
"Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."
"SAS Visual Analytics is expensive, as is the rest of the platform."
"The product is quite expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Computer Software Company
9%
Government
9%
Manufacturing Company
8%
Financial Services Firm
20%
Government
11%
Computer Software Company
10%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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?
Anaconda is an open-source tool, so I do not pay anything for it. It is compatible with every tool, regardless of whether it is open source or a paid package.
What needs improvement with Anaconda?
There is room for improvement, especially regarding deployment. The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools.
What do you like most about SAS Visual Analytics?
The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps w...
What is your experience regarding pricing and costs for SAS Visual Analytics?
It's about an average of five. It's easy to scale, but it comes with cost.
What needs improvement with SAS Visual Analytics?
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI. It may be that our current subscription does not include AI-enabled features, but I wo...
 

Also Known As

No data available
SAS BI
 

Overview

 

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms. Updated: June 2025.
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