Amazon SageMaker vs Anaconda comparison

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Amazon SageMaker

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Executive SummaryUpdated on Dec 5, 2024

Anaconda and Amazon SageMaker are competitors in the data science and machine learning sector, with SageMaker edging out in power due to its advanced features and AWS integration.

Features: Anaconda is notable for package dependency management, virtual environment creation, and a wide array of libraries for data analysis. Amazon SageMaker stands out with built-in data labeling, automatic model tuning, and seamless AWS integration, facilitating complete machine learning workflows.

Room for Improvement: Anaconda could enhance its features by providing more pre-built solutions and expanding Jupyter Notebook integrations. Additionally, improving the learning curve for beginners would be beneficial. SageMaker can improve user interface simplicity and broaden support for third-party tools. Enhancements in cost management transparency and usability documentation could also be advantageous.

Ease of Deployment and Customer Service: Anaconda offers straightforward deployments with robust community support, suitable for individual data scientists. Meanwhile, Amazon SageMaker provides complex, scalable deployments supported by AWS's extensive customer service, ideal for enterprise applications demanding scalability.

Pricing and ROI: Anaconda's free distribution model ensures lower setup costs, appealing to cost-conscious users with a swift ROI for small projects. Amazon SageMaker, with its pay-as-you-go pricing, incorporates higher initial costs, but its extensive features offer substantial long-term ROI, especially beneficial for large-scale projects.

To learn more, read our detailed Amazon SageMaker vs. Anaconda Report (Updated: April 2025).

Amazon SageMaker vs. Anaconda

April 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

Amazon SageMaker

Ranking in Data Science Platforms

3rd

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

AI Development Platforms (5th)

Anaconda

Ranking in Data Science Platforms

12th

Average Rating

8.2

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.9%, down from 9.7% compared to the previous year. The mindshare of Anaconda is 2.1%, up from 2.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

Create innovative assistants with seamless data integration for large-scale projects

The various integration options available in Amazon SageMaker ( /products/amazon-sagemaker-reviews ), such as Firehose for connecting to data pipelines, are simple to use. Tools like AWS Glue ( /products/aws-glue-reviews ) integrate well for data transformations. The Databricks ( /products/databricks-reviews ) integration aids data scientists and engineers. SageMaker is fully managed, offers high availability, flexibility with TensorFlow ( /products/tensorflow-reviews ), PyTorch ( /products/pytorch-reviews ), and MXNet ( /products/mxnet-reviews ), and comes with pre-trained algorithms for forecasting, anomaly detection, and more.

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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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Quotes from Members

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

Pros

"The evolution from SageMaker Classic to SageMaker Studio, particularly the UI part of Studio, is commendable."

"The few projects we have done have been promising."

"I recommend SageMaker for ML projects if you need to build models from scratch."

"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."

"The most tool's valuable feature, in my experience, is hyperparameter tuning. It allows us to test different parameters for the same model in parallel, which helps us quickly identify the configuration that yields the highest accuracy. This parallel computing capability saves us a lot of time."

"It's user-friendly for business teams as they can understand many aspects through the AWS interface."

"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."

"The most valuable feature of Amazon SageMaker for me is the model deployment service."

More Amazon SageMaker pros

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

"Voice Configuration and Environmental Management Capabilities are the most valuable features."

"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 virtual environment is very good."

"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 best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."

"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."

"The most valuable feature is the set of libraries that are used to support the functionality that we require."

More Anaconda pros

Cons

"The user interface (UI) and user experience (UX) of SageMaker and AWS, in general, need improvement as they are not intuitive and require substantial time to learn how to use specific services."

"When starting a new session, the waiting time can be quite long, ranging from two to five minutes."

"Amazon might need to emphasize its capabilities in generative models more effectively."

"The product must provide better documentation."

"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."

"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."

"AI is a new area and AWS needs to have an internship training program available."

"The platform could be more accessible to users with basic coding skills, making it more intuitive and easier for beginners to use comfortably."

More Amazon SageMaker cons

"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."

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

"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."

"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."

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

"It also takes up a lot of space."

"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."

More Anaconda cons

Pricing and Cost Advice

"Amazon SageMaker is a very expensive product."

"I would rate the solution's price a ten out of ten since it is very high."

"SageMaker is worth the money for our use case."

"Databricks solution is less costly than Amazon SageMaker."

"The support costs are 10% of the Amazon fees and it comes by default."

"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."

"There is no license required for the solution since you can use it on demand."

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

More Amazon SageMaker pricing and cost advice

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

"The licensing costs for Anaconda are reasonable."

"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."

"The tool is open-source."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Educational Organization

11%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

20%

Computer Software Company

Government

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

What do you like most about Amazon SageMaker?

We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...

What is your experience regarding pricing and costs for Amazon SageMaker?

The pricing is high, around an eight. However, SageMaker offers free trials for the first two months, allowing users to determine which features they need. It is considered value for money given it...

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.

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Product Reports

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Amazon SageMaker

May 2025

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May 2025

Also Known As

AWS SageMaker, SageMaker

No data available

Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

Amazon Web Services (AWS)

Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and provide open source assurance for packages in Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.

Python is the fastest growing language for data science. Anaconda includes 720+ Python open source packages and now includes essential R packages. This powerful combination allows you to do everything you want from BI to advanced modeling on complex Big Data

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

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