Vertex AI vs Amazon SageMaker

by Gralio Feb 25, 2025

Vertex AI and Amazon SageMaker are both powerful cloud-based machine learning platforms. Vertex AI prioritizes ease of use and Google Cloud integration, while SageMaker offers more advanced features, scalability, and AWS integration. Choosing between them depends on your business needs, technical expertise, and existing cloud infrastructure.

At Gralio.ai we help to simplify your decision-making process by offering detailed, side-by-side software comparisons like this one, to help you confidently choose the tool that aligns with your business goals.

This comparison was created by analysing 450 reviews and 60 websites, saving 3 hours of reading.

Vertex AI

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Amazon SageMaker

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About

Vertex AI is Google's cloud-based platform for building and using artificial intelligence. It provides tools for building AI models, even without coding experience, and connecting your data from various sources. Vertex AI makes it easier to deploy, manage, and scale your AI projects, helping you integrate AI into your business operations regardless of your current technical capabilities. It stands out by offering pre-trained models and a user-friendly interface for a smoother AI adoption experience.

Amazon SageMaker is a cloud-based platform that streamlines the process of creating, training, and deploying machine learning models. It provides all the tools needed for each stage, removing technical roadblocks and allowing businesses to leverage the power of machine learning regardless of their current expertise. This makes it easier for companies to use data for predictions, improving efficiency in various applications.

Summary

Main difference

Vertex AI excels in user-friendly AI tools and seamless integration with other Google services, making it ideal for businesses heavily invested in the Google ecosystem. Amazon SageMaker stands out with its extensive features, scalability, and deep integration with the AWS ecosystem, catering to businesses seeking advanced customization and AWS synergy.

Relative strengths of Vertex AI (compared to Amazon SageMaker)

Stronger Google ecosystem integration: Seamlessly integrates with BigQuery, Dataflow, and other Google Cloud services, simplifying data management and workflow.
User-friendly interface: Offers intuitive tools like AutoML, making it easier for beginners and non-coders to build and deploy models.
Pre-trained models and AutoML: Provides a rich library of pre-trained models and AutoML capabilities, accelerating development and reducing the need for extensive coding.

Relative weaknesses of Vertex AI (compared to Amazon SageMaker)

Less mature feature set: Offers fewer advanced features and customization options compared to SageMaker.
Steeper learning curve: While user-friendly for basic tasks, mastering advanced features can be challenging.
Pricing complexity: Can be difficult to estimate and manage costs, especially for large-scale projects.

Who should use Vertex AI VS. Amazon SageMaker

Vertex AI is a comprehensive machine learning platform perfect for businesses of all sizes wanting to leverage AI. Its user-friendly tools, like AutoML, make building models accessible even without coding. While some users find the platform complex and expensive, many praise its scalability and comprehensive features for managing the entire machine learning workflow.

Amazon SageMaker is a comprehensive machine learning platform ideal for businesses seeking to build, train, and deploy models efficiently. Its seamless integration with other AWS services is a major advantage, simplifying data management and deployment. Users praise its scalability and pre-built models, while some find pricing complex and the interface less intuitive.

Ideal for small, medium, and large enterprises.
Best fit for IT, software, and telecommunications, but also suitable for finance, healthcare, and education.

Best fit for enterprise companies.
Suitable for businesses across various industries leveraging AWS cloud services.

Vertex AI and Amazon SageMaker features

Supported

Partially supported

Not supported

Type in the name of the feature or in your own words tell us what you need

User-friendly AI tools

Supported

Vertex AI offers user-friendly tools like AutoML and pre-trained models, suitable for both experts and beginners.

Supported

SageMaker offers user-friendly tools like Canvas and Autopilot, democratizing AI development.
Cloud-based video conferencing

Not supported

Vertex AI does not offer video conferencing. It focuses on machine learning tasks.

Not supported

SageMaker does not support video conferencing. Consider Amazon Chime instead.
GPU training support

Supported

Vertex AI supports using GPUs for training Machine Learning models. It supports various NVIDIA GPUs like NVIDIA_H100_80GB, NVIDIA_A100_80GB, NVIDIA_TESLA_A100, NVIDIA_TESLA_P4, NVIDIA_TESLA_P100, NVIDIA_TESLA_T4, NVIDIA_TESLA_V100, and NVIDIA_L4. You can add one or more GPUs to A2 or N1 type VMs.

Supported

Amazon SageMaker fully supports GPU training for accelerated model training, offering various GPU instances, distributed training capabilities, and custom GPU-supported containers.
Edge deployment

Supported

Vertex AI enables deployment of models to edge devices through its AutoML Edge models. These models are specifically designed for edge devices with limited resources. Vertex AI offers flexibility in deployment methods and integrates with MLOps tools for streamlined model management.

Supported

Amazon SageMaker supports deploying models to edge devices, even those with limited resources, through features like SageMaker Neo for model optimization. While SageMaker Edge Manager, a dedicated service for this, is being discontinued, the core capabilities for edge deployment remain available.
3D visualizations

Not supported

Vertex AI does not support creation of 3D visualizations. This functionality is offered by a different product called "Vertex 3D Visualization Platform".

Supported

Amazon SageMaker, specifically its Ground Truth component, allows for the creation and visualization of 3D point cloud data and object detection. It supports labeling and visualizing 3D point cloud frames and sensor fusion with video data. While its geospatial capabilities lean towards 2D visualizations, it does offer tools for processing large-scale geospatial datasets.
AWS Trainium support

Not supported

Vertex AI does not support AWS Trainium instances for deep learning training.

Supported

Amazon SageMaker fully supports the utilization of AWS Trainium instances for deep learning training.

Qualities

Value and Pricing Transparency

-0.64

Rather negative sentiment

No data
Customer Service

+0.07

Neutral sentiment

No data
Ease of Use

+0.75

Strongly positive sentiment

No data
Reliability and Performance

+0.21

Neutral sentiment

No data
Ease of Implementation

+0.35

Rather positive sentiment

No data
Scalability

+0.56

Rather positive sentiment

No data

Vertex AI and Amazon SageMaker Pricing

No data

User sentiment

Rather negative

-0.64

See full Pricing page

No data

See full Pricing page

Vertex AI and Amazon SageMaker review insights

411 reviews analysed from

Users love

The AutoML feature is great for quickly building models without coding experience.
The platform scales well with large datasets, particularly when used with BigQuery.
Vertex AI simplifies the process of building and managing machine learning models.
Provides a comprehensive set of tools for an end-to-end machine learning workflow.

Highly scalable and compute-powerful, easily handles large datasets.
Seamless integration with other AWS services like S3, Lambda, and data storage solutions.
Provides built-in algorithms and frameworks that simplify model building.
Offers pre-trained models that expedite development for common tasks.
Easy to build, train, and deploy ML models at scale.
Supports distributed training and a variety of machine learning frameworks.
Wide range of instance types to optimize performance and cost.
Excellent for deploying models in production with features like A/B testing and autoscaling.

Users dislike

Can be complex sometimes and users are unsure if it performs correctly
The platform can be difficult to navigate for new users and has a steep learning curve.
The cost can get high quickly, making it difficult to stay within budget.
Customer support is not as extensive as some other machine learning platforms.

Difficult to estimate pricing accurately, even with the AWS pricing calculator.
Running larger models for testing purposes can lead to unexpected costs.
User interface is cluttered and feels like a client tool hosted on the web.
Limited control over CI/CD pipelines, could be more self-managed.
SageMaker Pipelines UI is less intuitive than alternatives like Airflow or Azure.
Studio and Image terminals are not as user-friendly as dedicated IDEs like IntelliJ.
Steep learning curve, especially for beginners without coding experience.
Limited documentation and online resources for troubleshooting and learning advanced features.
Can be expensive, especially for large projects or extended usage.

Vertex AI and Amazon SageMaker Ratings

G2

4.4/5

(419)
Glassdoor

3.5/5

(2)

G2

4.2/5

(39)
Glassdoor

3.7/5

(206324)

Company health

Employee growth

No data

11% increase in the last year

Web traffic

No data

10% increase in the last quarter

Financing

No data

How do Vertex AI's pre-trained models compare to SageMaker JumpStart's offerings?

Both Vertex AI and SageMaker JumpStart offer pre-trained models to accelerate development. While both provide various models, SageMaker JumpStart explicitly mentions sourcing models from AWS Marketplace and built-in algorithms, alongside its own offerings, potentially giving it a broader range. Vertex AI focuses on its own curated set of pre-trained models and AutoML capabilities. Choosing between them depends on the specific model needs and whether leveraging a marketplace or readily available algorithms is a priority.

Which platform better integrates with existing cloud services, GCP or AWS?

Amazon SageMaker, being an AWS product, more seamlessly integrates with existing AWS cloud services. This tight integration with services like S3, Lambda, and other AWS data storage solutions simplifies data access and management for machine learning workflows. While Vertex AI integrates with GCP services, SageMaker's native integration within the AWS ecosystem offers a more streamlined experience for users already invested in AWS.

What are the advantages of Vertex AI?

Vertex AI offers a more user-friendly experience, especially for those without coding experience, through its AutoML and pre-trained models. It simplifies the process of building and managing machine learning models, making AI adoption smoother. Vertex AI also integrates well with other Google Cloud services like BigQuery, offering advantages for users already within the Google ecosystem.

What are the disadvantages of Vertex AI?

Vertex AI can be difficult to navigate initially, presenting a steep learning curve for new users. Its cost can escalate quickly, making budgeting challenging. Finally, some users find customer support lacking compared to other machine learning platforms.

Alternatives to Vertex AI and Amazon SageMaker

Stream Chat

Stream Chat is a platform that helps you add chat, video calls, and activity feeds to your app. It provides the building blocks for these features, like pre-made components and code libraries, so you don't have to build everything from scratch. This saves your developers time and lets them focus on your app's unique features. Stream Chat is designed to handle a lot of users and messages, making it suitable for medium to large companies. They prioritize making integration easy for developers and ensuring the final product is reliable and scalable for businesses.

Chrome OS

Chrome OS is Google's operating system. It's known for being simple, fast, and secure, running on laptops called Chromebooks. It's particularly well-suited to businesses because it offers centralized management features, making it easy for IT departments to control and secure devices. Chrome OS is designed to work primarily with web-based applications and cloud storage, making it a good option for businesses looking to reduce reliance on traditional software.

SAS Visual Data Mining and Machine Learning

SAS Visual Data Mining and Machine Learning is a software suite that helps businesses uncover insights from their data. It offers tools for data preparation, visualization, and building predictive models using machine learning. Its intuitive visual interface and automated features make it accessible for users of varying technical skills, from data scientists to business analysts. The software allows for coding in multiple languages like Python and R, making it flexible for diverse teams. Its strength lies in automating complex processes, enabling faster and more informed business decisions.

Frontline Insights Platform

Frontline Insights Platform is a suite of connected software tools designed for K-12 education leaders in the USA. It aims to simplify school administration by integrating various functions like HR, business operations, and student management. The platform promises streamlined workflows, reduced data entry, and easier access to information through a single sign-on and unified interface. Frontline emphasizes data security and provides benchmarking data to compare your district's performance. Their focus is on providing a comprehensive solution for K-12 administrators, supporting better decision-making and improved efficiency.

Verizon Media SSP

Verizon Media SSP, formerly known as Flurry, is a free mobile app analytics platform. It helps app developers track key metrics like installs, user sessions, and time spent in-app. This data helps understand user behavior, optimize app performance, and make informed decisions to grow your app. Verizon Media SSP is suitable for developers of any size and boasts a user-friendly interface with powerful features like custom event tracking and data export.

SuperAnnotate

SuperAnnotate is a platform designed to speed up the process of building AI models using high-quality data. It provides tools for labeling images, videos, text, and audio, making it easier to create the training data that AI models need. SuperAnnotate also offers project management features, automation tools, and access to a marketplace of professional data annotation services to help streamline the entire model development process. It stands out for its strong security certifications and focus on data quality, making it a popular choice for businesses of all sizes.

Page co-authored by

Michal Kaczor

CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

Tymon Terlikiewicz

CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.

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