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: June 2025).

Amazon SageMaker vs. Anaconda

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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

2nd

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

11th

Average Rating

8.2

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.5%, down from 9.6% 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

"SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project."

"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."

"The product aggregates everything we need to build and deploy machine learning models in one place."

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

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

"The deployment is very good, where you only need to press a few buttons."

"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."

"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."

More Amazon SageMaker pros

"The most advantageous feature is the logic building."

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

"It provides a unified platform where you can install Jupyter, Python Spider, and other related tools without needing separate installations."

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

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

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

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

"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."

More Anaconda pros

Cons

"The solution needs to be cheaper since it now charges per document for extraction."

"Amazon SageMaker can make it simpler to manage the data flow from start to finish, such as by integrating data, usingthe machine, and deploying models. This process could be more user-friendly compared to other tools. I would also like to improve integration with Bedrock and the LLM connection for AWS."

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

"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."

"The main challenge with Amazon SageMaker is the integrations."

"I would recommend having more walkthrough videos and articles beyond AWS Skill Builder."

"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."

More Amazon SageMaker cons

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

"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."

"I think that the framework can be improved to make it easier for people to discover and use things on their own."

"It also takes up a lot of space."

"Anaconda can't handle heavy workloads."

"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 should be optimized for RAM consumption."

"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."

More Anaconda cons

Pricing and Cost Advice

"The product is expensive."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."

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

"You don't pay for Sagemaker. You only pay for the compute instances in your storage."

"The pricing could be better, especially for querying. The per-query model feels expensive."

"The pricing is comparable."

"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."

"On average, customers pay about $300,000 USD per month."

More Amazon SageMaker pricing and cost advice

"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."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

12%

Manufacturing Company

Educational Organization

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

Amazon SageMaker

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Also Known As

AWS SageMaker, SageMaker

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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

Amazon SageMaker vs. Anaconda