G2 Vendor Directory

Azure Machine Learning vs. Amazon SageMaker

A side-by-side comparison based on G2 review data.

MetricAzure Machine Learning

by Microsoft

Amazon SageMaker

by Amazon Web Services (AWS)

Overall rating4.34.3
Review count9057
Ease of use8.78.6
Ease of setup8.68.6
Quality of support8.88.9
Meets requirements8.78.9
NPS48.27586246.296296
Small Business33.3%30.9%
Mid-Market26.7%34.5%
Enterprise40.0%34.5%
Total page views239401
Total LLM citations1,0351,606

Azure Machine Learning

Azure Machine Learning is an enterprise-grade service that facilitates the end-to-end machine learning lifecycle, enabling data scientists and developers to build, train, and deploy models efficiently. Key Features and Functionality: - Data Preparation: Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric. - Feature Store: Increase agility in shipping your models by making features discoverable and reusable across workspaces.

Pros

  • Features
  • Ease of Use
  • Customer Support
  • Data Management
  • Implementation Ease
  • Efficiency

Amazon SageMaker

Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment.

Pros

  • Ease of Use
  • Implementation Ease
  • Model Management
  • Time-Saving
  • Features
  • Fast Processing