Hi All, I would like to gather feedback on the industry demand for an ML feature store catalog and whether it makes sense to develop this feature within Gravitino.
The attached proposal suggests adding ML Feature Store support to Gravitino, enabling it to serve as a unified metadata management layer. This would bridge the gap between data engineering and machine learning workflows. Feature store metadata naturally complements model metadata; since Gravitino already manages the underlying data assets from which features are derived, this addition would provide a more cohesive management layer. Please find the proposal document and the related GitHub issue below: ML Feature Store Proposal Document <https://docs.google.com/document/d/11NYd3KWxryCFxuG887kJ3d0p87leNyqK/edit?usp=sharing&ouid=114123410449326225963&rtpof=true&sd=true> GitHub Issue Link <https://github.com/apache/gravitino/issues/10594> Thank you. Regards, Akshay Thorat
