Amazon SageMaker Feature Store vs Hopsworks Feature Store

Amazon SageMaker Feature Store has no write-up on Specifiction yet; its figures are above.

Hopsworks Feature Store manages, reuses, and serves machine-learning features. It pairs an offline store based on Apache Hudi tables on HopsFS with an online RonDB key-value store. The platform can generate training datasets using feature values from a historical point in time, helping prevent data leakage. Its Feature Registry supports metadata search, automatic analysis and statistics, version comparison, and access control. Hopsworks tracks feature distributions, detects drift, and can send alerts. Listed integrations include Airflow, Apache Flink, Databricks, Snowflake, Spark, AWS SageMaker, Vertex AI, and Weights & Biases. Deployment options include managed SaaS, Kubernetes on AWS, Azure, or GCP, and air-gapped data centres. The installer documentation lists AWS EKS, Google GKE, Azure AKS, and OVHCloud, requires Kubernetes 1.27 or higher, and recommends at least four to five nodes. Security options described include encryption at rest and in transit, project-based access controls, two-factor authentication, and SSO. The free tier includes one project and community support; SaaS is pay as you go, while Enterprise pricing is custom.