Executive SummaryUpdated on Oct 8, 2024
Amazon SageMaker and Google Vertex AI are prominent machine learning platforms that compete in the cloud-based machine learning market. Users tend to favor Google Vertex AI due to its advanced feature set and user-friendly deployment over Amazon SageMaker, known for its extensive AWS integration but with some usability challenges.
Features: Amazon SageMaker provides robust integration with AWS services, comprehensive model training, and extensive deployment options. It supports a wide array of modeling tools that are ideal for different user needs within the AWS ecosystem. Google Vertex AI offers advanced AutoML capabilities, intuitive model customization options, and sophisticated toolsets that empower users seeking high-level functionalities.
Room for Improvement: Amazon SageMaker can enhance user experience by simplifying configurations and reducing deployment complexity, which presents a barrier for some users. It could also improve user documentation to assist in navigation. Google Vertex AI should focus on boosting its documentation and enhancing user support to help new users. Additionally, simplifying intricate features can make it more accessible.
Ease of Deployment and Customer Service: Amazon SageMaker offers a smooth deployment experience due to its integration with AWS, though the steep learning curve can be a hurdle. Users cite Google Vertex AI as having a more intuitive deployment process with responsive customer support, making it attractive for those seeking a quick and straightforward setup process.
Pricing and ROI: Amazon SageMaker's pricing aligns with AWS infrastructure costs, which may be familiar but potentially high, with ROI hinging on usage scale. Google Vertex AI provides competitive pricing that users find reasonable relative to its features, leading to a positive ROI for leveraging its capabilities extensively.
To learn more, read our detailed
Amazon SageMaker vs. Google Vertex AI Report (Updated: December 2024).
