Amazon SageMaker vs Anaconda comparison

Read 18 Anaconda reviews

1,469 Views
1,198 Comparison Views

95% willing to recommend

Amazon SageMaker

Comparison Buyer's Guide

Download the report

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: March 2025).

Amazon SageMaker vs. Anaconda

Download the complete report

Helped 845,040 peers since 2012

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

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 April 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.3%, down from 9.8% compared to the previous year. The mindshare of Anaconda is 2.1%, down from 2.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Hemant Paralkar

Lead Consultant at Saama

Improves team collaboration with advanced feature sharing but needs a better user experience

Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.

Read full review

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.

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

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

"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."

"The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook."

"Allows you to create API endpoints."

"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."

"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 these models, making accessing them convenient as needed."

"The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases."

"The tool makes our ML model development a bit more efficient because everything is in one environment."

More Amazon SageMaker pros

"The most advantageous feature is the logic building."

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

"The solution is stable."

"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."

"It has a lot of functionality available, supports many libraries, and the developers are continually improving it."

"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."

"The notebook feature is an improvement over RStudio."

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

More Anaconda pros

Cons

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

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

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

"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."

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

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

"SageMaker would be improved with the addition of reporting services."

"Improvements are needed in terms of complexity, data security, and access policy integration in Amazon SageMaker."

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

"Anaconda can't handle heavy workloads."

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

"Anaconda should be optimized for RAM consumption."

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

"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."

"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."

More Anaconda cons

Pricing and Cost Advice

"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."

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

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

"Amazon SageMaker is a very expensive product."

"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."

"The tool's pricing is reasonable."

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

"The solution is relatively cheaper."

More Amazon SageMaker 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."

"The tool is open-source."

"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."

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

845,040 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

19%

Educational Organization

13%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

20%

Computer Software Company

Manufacturing Company

University

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?

Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.

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 does not require a pricing structure, and it is available as an open-source tool. The features of Python, Jupyter, and others are free to use.

What needs improvement with Anaconda?

Anaconda consumes a significant amount of processing memory when working on it. This is something that needs improvement as it can impact performance.

Databricks vs Amazon SageMaker

Comparisons

Compared 17% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Dataiku vs Amazon SageMaker

Compared 10% of the time

Google Vertex AI vs Amazon SageMaker

Compared 9% of the time

Cloudera Data Science Workbench vs Amazon SageMaker

Compared 3% of the time

More Amazon SageMaker Competitors

Databricks vs Anaconda

Compared 35% of the time

Microsoft Power BI vs Anaconda

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs Anaconda

Compared 8% of the time

KNIME vs Anaconda

Compared 5% of the time

MathWorks Matlab vs Anaconda

Compared 4% of the time

More Anaconda Competitors

Product Reports

Amazon SageMaker

Download Amazon SageMaker product report

Download Anaconda product report

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

Amazon SageMaker vs. Anaconda