Amazon SageMaker vs TensorFlow comparison

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Amazon SageMaker

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Executive SummaryUpdated on Dec 4, 2024

TensorFlow and Amazon SageMaker compete in the field of machine learning, with TensorFlow being an open-source framework and SageMaker offering a fully managed service. TensorFlow stands out in ease of use and flexibility, while Amazon SageMaker is praised for integrated tools and a robust service ecosystem.

Features: TensorFlow provides deep learning support, flexibility for customization, and a large community backing for problem-solving. SageMaker offers automatic model tuning, integrated Jupyter notebooks, and built-in algorithms for quick model deployment.

Room for Improvement: TensorFlow could enhance its deployment processes to ease infrastructure management, improve documentation for user-friendliness, and streamline community support channels. SageMaker might reduce the complexity of transitioning for users not deeply rooted in AWS, optimize cost management tools, and expand beyond existing AWS dependencies for wider appeal.

Ease of Deployment and Customer Service: TensorFlow demands users to manage their infrastructure, which adds complexity for less technical users. Amazon SageMaker simplifies deployment through AWS with pre-configured instances and comprehensive documentation, combined with responsive AWS customer support.

Pricing and ROI: TensorFlow, being open-source, offers low initial setup costs and favorable ROI when leveraging existing resources. SageMaker involves costs linked to AWS resources, possibly leading to higher upfront expenses, but its managed services can result in long-term savings by lowering operational overhead.

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

Amazon SageMaker vs. TensorFlow

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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 AI Development Platforms

5th

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Data Science Platforms (3rd)

TensorFlow

Ranking in AI Development Platforms

6th

Average Rating

8.8

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the AI Development Platforms category, the mindshare of Amazon SageMaker is 5.5%, down from 8.5% compared to the previous year. The mindshare of TensorFlow is 3.8%, down from 6.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development 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

Ashish Upadhyay

Founder at BlockMosiac

A robust tools for model visualization and debugging with superior scalability and stability, and an intuitive user-friendly interface

The one feature we find most valuable at our company is its robust and flexible machine-learning capabilities. It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions. The ability to develop and fine-tune models, such as risk assessment for detection and market protection, as well as the creation of recommendation systems, is paramount. This versatility extends to providing personalized identity-relevant applications for our enterprise clients, delivering valuable insights to the market. Its exceptional support for deep learning and its efficient resource utilization enable us to undertake complex financial and data analyses. The flexibility it provides is crucial for meeting industrial requirements and crafting solutions tailored to our client's specific needs.

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 superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."

"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."

"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 few projects we have done have been promising."

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

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

"The technical support from AWS is excellent."

"We were able to use the product to automate processes."

More Amazon SageMaker pros

"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."

"The available documentation is extensive and helpful."

"Google is behind TensorFlow, and they provide excellent documentation. It's very thorough and very helpful."

"It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions."

"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."

"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."

"It's got quite a big community, which is useful."

"I would rate the solution an eight out of ten. I am not a developer but more of an account manager. I can find what I want with TensorFlow. I haven’t contacted technical support for any issues. Since TensorFlow is vastly documented on the internet, I usually find some good websites where people exchange their views about the solution and apply that."

More TensorFlow pros

Cons

"The product must provide better documentation."

"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."

"The model repository is a concern as models are stored on a bucket and there's an issue with versioning."

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

"The entry point can be a bit difficult. Having all documentation easily accessible on the front page of SageMaker would be a great improvement."

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

"The solution is complex to use."

"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."

More Amazon SageMaker cons

"There are a lot of problems, such as integrating our custom code. In my experience model tuning has been a bit difficult to edit and tune the graph model for best performance. We have to go into the model but we do not have a model viewer for quick access."

"Personally, I find it to be a bit too much AI-oriented."

"I would love to have a user interface like a programming interface. You need to have a set of menus where you can put things together in a graphical interface. The complete automation of the integration of the modules would also be interesting. It’s more like plumbing as opposed to a fully automated environment."

"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."

"The process of creating models could be more user-friendly."

"The solution is hard to integrate with the GPUs."

"It would be nice if the solution was in Hungarian. I would like more Hungarian NAT models."

"There are connection issues that interrupt the download needed for the data sets. We need to prepare them ourselves."

More TensorFlow cons

Pricing and Cost Advice

"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."

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

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

"The tool's pricing is reasonable."

"Amazon SageMaker is a very expensive product."

"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."

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

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

More Amazon SageMaker pricing and cost advice

"It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."

"The solution is free."

"I rate TensorFlow's pricing a five out of ten."

"I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."

"We are using the free version."

"I did not require a license for this solution. It a free open-source solution."

"TensorFlow is free."

"I am using the open-source version of TensorFlow and it is free."

More TensorFlow pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Educational Organization

11%

Computer Software Company

11%

Manufacturing Company

13%

Computer Software Company

13%

University

Educational Organization

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 TensorFlow?

It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions.

What is your experience regarding pricing and costs for TensorFlow?

I am not familiar with the pricing setup cost and licensing.

What needs improvement with TensorFlow?

Providing more control by allowing users to build custom functions would make TensorFlow a better option. It currently offers inbuilt functions, however, having the ability to implement custom libr...

Databricks vs Amazon SageMaker

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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)

TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

Sample Customers

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

Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm

Amazon SageMaker vs. TensorFlow