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Amazon SageMaker vs OpenVINO comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 2024

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
4th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
36
Ranking in other categories
Data Science Platforms (3rd)
OpenVINO
Ranking in AI Development Platforms
14th
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2025, in the AI Development Platforms category, the mindshare of Amazon SageMaker is 6.1%, down from 8.7% compared to the previous year. The mindshare of OpenVINO is 1.6%, down from 3.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Hemant Paralkar - PeerSpot reviewer
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.
reviewer1530384 - PeerSpot reviewer
Open-source, easy to integrate, and perfectly tailored to the Movidius chipset
Generally, when you deploy edge products, it's really about latency. It's about getting that camera input, being able to process it, extracting the information you need, and getting the solution back to the person who made the request. Although I'm not necessarily saying its latency or accuracy is bad, it's always something that can be improved upon. By focusing on improving these areas, they can make the overall solution even better. At this point, the product could probably just use a greater integration with more machine learning model tools. However, that's not advice from experience per se. That's always just helpful in general. To be able to incorporate more models into the product makes it stronger. Therefore, to be clear, it's not coming from a point of a current deficiency. It's just a general comment.

Quotes from Members

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

Pros

"The technical support from AWS is excellent."
"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."
"I recommend SageMaker for ML projects if you need to build models from scratch."
"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 tool makes our ML model development a bit more efficient because everything is in one environment."
"I appreciate the ease of use in Amazon SageMaker."
"The deployment is very good, where you only need to press a few buttons."
"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."
"The inferencing and processing capabilities are quite beneficial for our requirements."
"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."
"The initial setup is quite simple."
 

Cons

"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."
"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."
"Amazon might need to emphasize its capabilities in generative models more effectively."
"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."
"The dashboard could be improved by including more features and providing more information about deployed models, their drift, performance, scaling, and customization options."
"Improvements are needed in terms of complexity, data security, and access policy integration in Amazon SageMaker."
"The solution is complex to use."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult."
"The model optimization is a little bit slow — it could be improved."
 

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."
"The support costs are 10% of the Amazon fees and it comes by default."
"On average, customers pay about $300,000 USD per month."
"The pricing could be better, especially for querying. The per-query model feels expensive."
"Databricks solution is less costly than Amazon SageMaker."
"The product is 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."
"We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
14%
Computer Software Company
11%
Manufacturing Company
9%
Manufacturing Company
45%
University
9%
Computer Software Company
7%
Financial Services Firm
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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.
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Comparisons

 

Also Known As

AWS SageMaker, SageMaker
No data available
 

Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
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Find out what your peers are saying about Amazon SageMaker vs. OpenVINO and other solutions. Updated: January 2025.
838,713 professionals have used our research since 2012.