Amazon SageMaker Feature Store vs Feathr

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

Feathr is a free, open-source platform for building and sharing data features used in machine-learning workflows. Its Python client supports custom functions alongside PySpark and Spark SQL, and a unified API runs transformations in batch, streaming, or online settings. Feature operations include time-based aggregations, sliding-window joins, lookups, and derived features. Feathr joins computed features to training data with point-in-time correctness to help reduce data leakage. An optional registry and UI support feature search, metadata and lineage review, sharing, and access management; registry backends include Azure Purview and ANSI SQL. Integrations include Azure and AWS storage, Snowflake, Kafka, Redis, Databricks, and Azure Synapse, as well as Azure Machine Learning and notebook tools. The project documents Azure, Databricks, and Synapse deployment, a Docker sandbox, and a locally installable Python client. It runs on Linux and web, and supports self-hosted and API use. The repository specifies Apache License 2.0. The FAQ notes that preprocessing currently appears limited to one UDF function, and feature-level access control is not supported yet.