"ML data" could be just about anything: images, sounds, graphs, tabular data, vectors. Depending on what your data is, you might end up with very different stor

"ML data" could be just about anything: images, sounds, graphs, tabular data, vectors. Depending on what your data is, you might end up with very different storage solutions. Though I think one common approach is to just dump most data in an S3-compatible datastore of your choice (there's seaweedfs or ceph, or the cloud provider of your choice). Specialized databases make a lot of sense when you need features like vector similarity search though.