Amazon Web Services (AWS) Reviews, Ratings & Features 2026 | Gartner Peer Insights

Gartner defines AI platforms for data science and machine learning (DSML) as platforms that support end-to-end AI model and agent development and life cycle management using diverse data science and AI techniques. These platforms enable data preparation, model building, deployment and governance, and are delivered as fully managed cloud services or on-premises infrastructure for AI experts and business users.

AI platforms for DSML primarily target AI experts, including data scientists and AI engineers, providing a comprehensive suite of data science and AI techniques for augmented and automated decision making. These platforms support building models using data-intensive methods such as machine learning, as well as techniques such as simulation and optimization. They handle all types of data — tabular, image, video and text — for multimodal applications, such as computer vision, natural language processing (NLP) or composite AI, that combines optimization with machine learning.

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AI Platforms for Data Science and Machine Learning

Amazon SageMaker AI

Amazon Web Services (AWS)

Manager, It Security And Risk Management

Valoro mucho este servicio de forma individual porque hemos sido capaz de cubrir todo el servicio de machine learning pudiendo crear el servicio, entrenarlo y desplegar modelos sin tocar nuestra insfraestructura fisica.
Sin embargo aprender como funciona nos ha traido mas de un disgusto...

I highly value this service individually because we've been able to cover the entire machine learning service, creating, training, and deploying models without touching our physical infrastructure.  However, learning how it works has brought us more than a few headaches...

<50M USD

50M - 250M USD

500M - 1B USD

250M - 500M USD

3B - 10B USD

1B - 3B USD

10B - 30B USD

30B + USD

Gov't/PS/ED <5,000 Employees

Gov't/PS/ED 5,000 - 50,000 Employees

Gov't/PS/ED 50,000 + Employees

SENIOR SYSTEMS ENGINEER

We have a lot of data and are trying to prototype ML models to train them on our datasets. We hope that the models we train will help us to boost efficiency of our processes and improve our infrastructure. 

Data And Analytics Manager

Using AWS Sagemaker has been a gamechanger for my organization's data science workflows delivering seamless end to end automation prioritizing streamlined collaboration and rapid iteration.  Huge focus on governance and training makes it a robust choice for scalable MLOps.

Google

Databricks

Microsoft

Cloudera

Anaconda

DataRobot

Alteryx

Dataiku

H2O.ai

Snowflake

Oracle

Other...

Alibaba Cloud

BigML

1010data

Domino Data Lab

NVIDIA (Run:ai)

4Paradigm

IBM (Red Hat)

Adamatics

Qlik

Intel

KNIME

Neo4j

Activeeon

JFrog

Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.

Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. The ultimate benefit of cloud computing, and AWS, is the ability to leverage a new business model and turn capital infrastructure expenses into variable costs. Businesses no longer need to plan and procure servers and other IT resources weeks or months in advance. Using AWS, businesses can take advantage of Amazon's expertise and economies of scale to access resources when their business needs them, delivering results faster and at a lower cost. Today, Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. With data center locations in the U.S., Europe, Singapore, and Japan, customers across all industries are taking advantage of our low cost, elastic, open and flexible, secure platform.

Reviews

Ratings Overview

Overall experience with

Favorable Review

AWS Sagemaker Streamlines Iteration and Collaboration in MLOps Amid Cost Challenges

Critical Review

Sagemaker Enables Efficient Data Handling Yet Complexity and Platform Dependency Noted

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