Anaconda Business vs Darwin comparison

Anaconda and SparkCognition are both solutions in the Data Science Platforms category. Anaconda is ranked #11 with an average rating of 8.7, while SparkCognition is ranked #26. Anaconda holds a 2.1% mindshare in Data Science Platforms, compared to SparkCognition’s 0.5% mindshare. Additionally, 95% of Anaconda users are willing to recommend the solution, compared to 100% of SparkCognition users who would recommend it.

Anaconda Business

Read 19 Anaconda Business reviews

1,619 Views
1,214 Comparison Views

95% willing to recommend

Darwin

Read 8 Darwin reviews

316 Views
316 Comparison Views

100% willing to recommend

Anaconda Business

Darwin

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 27, 2025

Anaconda Business and Darwin compete in the data science and machine learning domain. Darwin holds an advantage with its advanced features that can justify a higher cost.

Features: Anaconda Business offers extensive library support, seamless integration with Python, and enhanced package management and environment control. Darwin provides robust automated machine learning tools, an intuitive platform for model deployment, and caters to both seasoned data scientists and newcomers.

Room for Improvement: Anaconda Business could benefit from expanding pre-built features and ensuring easy model customization. Darwin could improve by simplifying deployment processes and expanding its training resources.

Ease of Deployment and Customer Service: Deployment with Anaconda Business is straightforward, with quick setup and effective environment management. Its customer service is responsive and practical. Darwin's deployment is slightly more complex, but it offers a reliable support system with a comprehensive set of resources and training materials.

Pricing and ROI: Anaconda Business has favorable upfront costs with a strong return on investment, especially for Python-centric workflows. Darwin's pricing is higher but aligns with its advanced feature set, providing significant long-term benefits in scenarios requiring automated processing and complex model handling.

To learn more, read our detailed Anaconda Business vs. Darwin Report (Updated: July 2025).

Buyer's Guide

Anaconda Business vs. Darwin

July 2025

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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

11th

Average Rating

8.2

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Darwin

Ranking in Data Science Platforms

26th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of Anaconda Business is 2.1%, up from 2.1% compared to the previous year. The mindshare of Darwin is 0.5%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Rohan Sharma

AI/ML Co-Lead at Developer Student Clubs - GGV

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.

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AaronCooke

Founder at Helio Summit

Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows.

There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do. Because it's so much better than traditional methods, we don't get a ton of complaints of, "Oh, we wish we could do that." Most people are happy to see that they can build models that quickly, and that it can be done by the people who actually understand the problem, i.e. SMEs, rather than having to rely on data scientists. There's a small learning curve, but it's shorter for an SME in a given industry to learn Darwin than it takes for data scientists to learn industry-specific problems. The industry I work in deals with tons and tons of data and a lot of it lends itself to Darwin-created solutions. Initially, there were some limitations around the size of the datasets, the number of rows and number of columns. That was probably the biggest challenge. But we've seen the Darwin product, over time, slowly remove those limitations. We're happy with the progress they've made.

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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."

"I can use Anaconda for non-heavy tasks."

"Anaconda is an open-source platform that can integrate numerous other kits and models in one place."

"The documentation is excellent and the solution has a very large and active community that supports it."

"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 notebook feature is an improvement over RStudio."

"The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results."

"It helped us find find the optimal area for where our warehouse should be located."

More Anaconda Business pros

"The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types."

"Darwin has increased efficiency and productivity for our company. With our risk management team, there were models that took them more than three days to process each, only to see the outcome. Now, it takes minutes for Darwin to process the current model. So, we can have it in minutes. We don't have to wait three days for all the models to be tested, then make a decision."

"The most valuable feature is the model-generation. With a nice dataset, Darwin gives you a nice model. That's a really nice feature because, if we're doing that ourselves, it's trial and error; we change the parameters a little and try again. We save time by just giving the dataset to Darwin and letting Darwin generate a model. We find the models it generates are good; better than we can generate."

"The thing that I find most valuable is the ability to clean the data."

"In terms of streamlining a lot of the low-level data science work, it does a few things there."

"The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science."

"I liked the data checking feature where it looks at your data and sees how viable it is for use. That's a really cool feature. Automatic assessment of the quality of datasets, to me, seems very valuable."

"I find it quite simple to use. Once you are trained on the model, you can use it anyway you want."

Cons

"When you install Anaconda for the first time, it's really difficult to update it."

"Having a small guide or video on the tool would help learn how to use it and what the features are."

"Anaconda consumes a significant amount of processing memory when working on it."

"The interface could be improved. Other solutions, like Visual Studio, have much better UI."

"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 process could be streamlined as the number of actions needed to deploy is quite large compared to other tools."

"It also takes up a lot of space."

"Anaconda should be optimized for RAM consumption."

More Anaconda Business cons

"The challenge is very big toward making models operational or to industrialize them. E.g., what we want to do is to make unique credit models for each customer. So, we are preparing the types of customers who we can try new credit models on Darwin. But, I see this still very challenging to be able to get the data sets so Darwin can work. At this point, we are working it to get the data sets ready for Darwin."

"The Read Me's and the tutorials need to be greatly improved to get customers to understand how things work. It might be helpful to have some sample data sets for people to play around with, as well as some tutorial videos. It was very hard to find information on this in the time crunch that we had, to see how it worked and then make it work, while interfacing with folks at SparkCognition."

"There are issues around the ethics of artificial intelligence and machine learning. You need to have a lot of transparency regarding what is going on under the hood in order to trust it. Because so much is done under the hood of Darwin, it is hard to trust how it gets the answers it gets."

"Something they are working on, which is great, is to have an API that can access data directly from the source. Currently, we have to create a specific dataset for each model."

"Our main data repository is on AWS. The trouble we are having is that we have to download the data from our repository to bring it into Darwin. It would be great if there was an API to connect our repository to Darwin."

"The analyze function takes a lot of time."

"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."

"An area where Darwin might be a little weak is its automatic assessment of the quality of datasets. The first results it produces in this area are good, but in our experience, we have found that extra analysis is needed to produce an extra-clean set of data."

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 tool is open-source."

"The product is open-source and free to use."

"The licensing costs for Anaconda are reasonable."

"My company uses the free version of the tool. There is also a paid version of the tool available."

"The license cost is not cheap, especially not for markets like Mexico. But sometimes, you do have to make these leap of faith for some tools to see if they can get you the disruption that you are aiming for. The investment has paid off for us very well."

"In just six months, we calculated six million pesos that we have prevented in revenue from going away with another customer because of this solution. Thanks to Darwin, we didn't lose those six million pesos."

"As far as I understand, my company is not paying anything to use the product."

"I believe our cost is $1,000 per month."

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Manufacturing Company

University

Computer Software Company

No data available

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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?

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.

See all answers

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.

See all answers

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Comparisons

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Amazon SageMaker vs Anaconda Business

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IBM SPSS Statistics vs Anaconda Business

Compared 7% of the time

Google Cloud Datalab vs Anaconda Business

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Databricks vs Darwin

Compared 59% of the time

IBM Watson Studio vs Darwin

Compared 41% of the time

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Product Reports

Buyer's Guide

Anaconda Business

August 2025

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Buyer's Guide

Darwin

August 2025

Download Darwin product report

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

SparkCognition builds leading artificial intelligence solutions to advance the most important interests of society. We help customers analyze complex data, empower decision making, and transform human and industrial productivity with award-winning machine learning technology and expert teams focused on defense, IIoT, and finance.

SparkCognition

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone

Hunt Oil, Hitachi High-Tech Solutions

Buyer's Guide

Anaconda Business vs. Darwin

July 2025

Free Report: Anaconda Business vs. Darwin

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