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Amazon SageMaker vs OpenVINO comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 2024
 

Categories and Ranking

Amazon SageMaker
Ranking in AI Development Platforms
4th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
32
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 December 2024, in the AI Development Platforms category, the mindshare of Amazon SageMaker is 8.1%, down from 8.7% compared to the previous year. The mindshare of OpenVINO is 2.3%, down from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Natu Lauchande - PeerSpot reviewer
Easy to use and manage, but the documentation does not have a lot of information
SageMaker Studio sounds very interesting. Feature Store and data pipeline features are very interesting. The product is a one-stop shop. It allows people without much engineering knowledge to try out and deploy models in environments similar to the production environments. The tool makes our ML model development a bit more efficient because everything is in one environment. It is easy to manage compared to when things were in different components of AWS. Amazon SageMaker is in AWS, so I need not pay two bills. It is one less system to manage, so it is easier.
ZM
A free toolkit providing improved neural network performance
The model optimization is a little bit slow — it could be improved. They should introduce some type of deep learning accelerator, like Jetson Xavier NX. There is a lacking in vehicle recognition — types of vehicles. Differentiating between cars, SUVs and different types of light, heavy, and medium trucks can be tricky. We have to train such models ourselves and then transfer them onto OpenVINO.

Quotes from Members

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

Pros

"The product aggregates everything we need to build and deploy machine learning models in one place."
"The tool makes our ML model development a bit more efficient because everything is in one environment."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."
"They are doing a good job of evolving."
"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."
"Allows you to create API endpoints."
"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."
"The initial setup is quite simple."
"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 inferencing and processing capabilities are quite beneficial for our requirements."
 

Cons

"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."
"Lacking in some machine learning pipelines."
"When starting a new session, the waiting time can be quite long, ranging from two to five minutes."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"AI is a new area and AWS needs to have an internship training program available."
"SageMaker would be improved with the addition of reporting services."
"The solution needs to be cheaper since it now charges per document for extraction."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
"The model optimization is a little bit slow — it could be improved."
"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."
 

Pricing and Cost Advice

"The pricing is comparable."
"The pricing could be better, especially for querying. The per-query model feels 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."
"SageMaker is worth the money for our use case."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"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."
"On average, customers pay about $300,000 USD per month."
"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
47%
University
8%
Computer Software Company
8%
Financial Services Firm
5%
 

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?
Pricing is rated as a six, which is slightly more expensive compared to the budget yet adequate for the capabilities provided. On average, customers pay about $300,000 USD per month.
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Comparisons

 

Also Known As

AWS SageMaker, SageMaker
No data available
 

Learn More

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Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
Information Not Available
Find out what your peers are saying about Amazon SageMaker vs. OpenVINO and other solutions. Updated: December 2024.
824,067 professionals have used our research since 2012.