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Anaconda Business vs SAP Predictive Analytics [EOL] comparison

Anaconda and SAP are both solutions in the Data Science Platforms category. Anaconda is ranked #7 with an average rating of 8.6, while SAP is ranked #27. Anaconda holds a 2.2% mindshare in Data Science Platforms, compared to SAP’s 1.4% mindshare. Additionally, 96% of Anaconda users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.
Anaconda Business
Read 29 Anaconda Business reviews
  • 2,569 Views
  • 2,004 Comparison Views
96% willing to recommend
SAP Predictive Analytics [EOL]
Read 3 SAP Predictive Analytics [EOL] reviews
  • 783 Views
  • 775 Comparison Views
100% willing to recommend
 

Comparison Buyer's Guide

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Executive SummaryUpdated on Apr 15, 2026

Anaconda Business and SAP Predictive Analytics [EOL] compete in the data analytics space. Anaconda Business has a pricing advantage due to its open-source nature, while SAP Predictive Analytics [EOL] offers more comprehensive features, providing potentially greater value.

Features: Anaconda Business is recognized for its open-source flexibility, which allows for extensive customization. It provides a wide library of data science packages and supports rapid innovation in Python and R environments. SAP Predictive Analytics [EOL] offers automated analytics capabilities, model management, and seamless integration with enterprise systems.

Ease of Deployment and Customer Service: Anaconda Business allows straightforward deployment with comprehensive support, ensuring smooth system integration. SAP Predictive Analytics [EOL] requires more effort during setup but offers robust customer service to address complex enterprise needs.

Pricing and ROI: Anaconda Business offers a cost-effective solution, leveraging its open-source platform and lower initial costs for rapid ROI. SAP Predictive Analytics [EOL] involves higher initial expenses, but its advanced features are viewed as providing substantial long-term ROI through better analytics and integration capabilities.

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April 2026
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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
SAP Predictive Analytics [EOL]
Ranking in Data Science Platforms
27th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 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 SAP Predictive Analytics [EOL] is 1.4%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Anaconda Business2.2%
SAP Predictive Analytics1.4%
Other96.4%
Data Science Platforms
 

Featured Reviews

reviewer2775498 - PeerSpot reviewer
reviewer2775498
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.
Read full review
Gary Cook - PeerSpot reviewer
Gary Cook
Executive at Empowered Analytics
Enables us to forecast and pull trends and has an easy installation
My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.
Read full review

Quotes from Members

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

Pros

"It has a lot of functionality available, supports many libraries, and the developers are continually improving it."
"The documentation is excellent and the solution has a very large and active community that supports it."
"The Python libraries are all readily available and there is no need to install anything separately."
"We find the advanced security, governance, and collaborative features for organizations using Python and R particularly useful, as these business plans provided by Anaconda Business have been very helpful."
"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."
"Anaconda Business has positively impacted my organization by easing the burden of querying large datasets that would otherwise slow down our work when using Excel, and since switching to Anaconda Business, I have improved productivity by around 80%, saving time in data crunching and exploration."
"Anaconda Business offers excellent visualization tools including Visual Studio, comprehensive analysis tools, and Python language analysis that significantly helps with building analysis and machine learning models."
"This is a product that I encourage people to use."
More Anaconda Business pros
"I have found that the solution is very stable."
"The most valuable features are the analytics and reporting."
"We always purchase SAP support because it is very good."
"SAP Predictive Analytics is better suited for business users because it hides the complexity of the model, whereas Microsoft Azure Machine Learning provides a lot more flexibility for technical professionals to tweak the model."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
 

Cons

"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 Business can be improved by offering faster package updates, an enhanced user interface, better cloud integration, more detailed analytics, and improved collaboration tools."
"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."
"My suggestion for improvement is that they should enhance the security point of view; it's good, but it needs some more advanced features."
"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."
"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."
"Sometimes the environment creation or package installation feels a bit slow, especially with bigger libraries."
More Anaconda Business cons
"This solution works for acquired data but not live, real-time data."
"This solution works for acquired data but not live, real-time data."
"The license fee appears to be prohibitively expensive and overly secretive, leading our clients to opt for cloud-based solutions that only charge for data storage and processing time."
 

Pricing and Cost Advice

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

By visitors reading reviews
Financial Services Firm
16%
University
11%
Manufacturing Company
7%
Computer Software Company
7%
No data available
 

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.
See all answers
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.
See all answers
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.
See all answers
Ask a question
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Product Reports

Buyer's Guide
Anaconda Business
April 2026
Anaconda Business reportDownload Anaconda Business product report
Buyer's Guide
Data Science Platforms
April 2026
SAP Predictive Analytics [EOL] reportDownload SAP Predictive Analytics [EOL] product report
 

Also Known As

No data available
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Overview

Anaconda Business provides a comprehensive platform for data science applications, integrating extensive libraries and seamless Python and R compatibility, enhancing developer productivity.

Anaconda Business offers data science professionals a platform combining extensive library support with pre-built models and seamless integration of Python and R environments. With features like a user-friendly interface and integrated Jupyter Notebook, it facilitates real-time code execution and debugging. Environmental management is simplified via Conda, while cloud-based access and package management enhance user experience. Community support and integration with applications like RStudio and Jupyter aid in data science and deep learning tasks.

What are the key features of Anaconda Business?
  • Extensive Library Support: Access numerous libraries for enhanced development capabilities.
  • Seamless Python and R Integration: Foster productivity through combined language support.
  • Cloud-Based Access: Facilitate collaboration and accessibility across teams.
  • Jupyter Notebook Integration: Enable real-time code execution and debugging.
  • Conda Environment Management: Simplify setup and management of environments.
What benefits should be considered in Anaconda Business?
  • Efficient Development: Streamline workflows with comprehensive tool integration.
  • Enhanced Collaboration: Utilize cloud-based tools for teamwork and data sharing.
  • Scalability: Adapt to growing workloads with robust capabilities.
  • Community Support: Leverage community expertise for solutions and troubleshooting.

Anaconda Business is widely used in industries like machine learning and data analysis, where it's employed for tasks such as predictive modeling and data visualization. Organizations utilize its compatibility with tools like Scikit-learn and TensorFlow for creating statistical models, supporting applications in fields such as analytics, education, subrogation, and warehouse management.

Anaconda

SAP Predictive Analytics [EOL] offered a powerful platform for creating predictive models that supported business decision-making by utilizing historical data to anticipate future trends.

SAP Predictive Analytics [EOL] was designed to integrate with existing SAP environments, allowing businesses to leverage their existing data infrastructure. It provided users with intuitive tools to automate data preparation and model management, simplifying complex analytical processes. Data scientists could efficiently build and deploy predictive models to address specific business questions. SAP emphasized ease of deployment and scalability, ensuring the platform met the needs of data-driven enterprises.

What are the key features?
  • Automated Model Creation: Streamlines the process of generating predictive models, reducing time and effort.
  • Data Preparation: Simplifies data cleaning and preparation, ensuring high-quality input for analysis.
  • Seamless Integration: Easily integrates with SAP environments, enhancing data accessibility.
What benefits should users consider in reviews?
  • Informed Decision-Making: Provides insights that help businesses make data-informed decisions.
  • Efficiency in Analysis: Reduces the time needed to develop and deploy predictive models.
  • Scalability: Supports expanding data needs as businesses grow.

In industries like manufacturing and retail, SAP Predictive Analytics [EOL] helped optimize supply chains and inventory management by forecasting demand trends. Financial sector users implemented it to enhance risk analysis and fraud detection models, providing valuable insights for mitigating potential risks.

SAP
 

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
mBank
Buyer's Guide
Data Science Platforms
April 2026
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