Amazon SageMaker’s biggest strength is that it delivers a fully managed, end-to-end machine learning (ML) environment within AWS’s secure ecosystem. It covers the whole workflow, from data preparation and model training to deployment and ongoing monitoring. For teams, this can save a huge amount of time by abstracting away infrastructure complexity, while still providing powerful distributed training capabilities, including features like HyperPod. Review collected by and hosted on G2.com.

Opaque pricing. Costs can escalate quickly, especially with long-running jobs or larger deployments. I’ve also seen “month-end shock” because the billing model isn’t clear or predictable. Review collected by and hosted on G2.com.