Data storage requirements for AI vary widely according to the application and the source material.
The filesystem is the foundational layer of storage. Its fundamental unit is a “file” — which can be text or binary, is not versioned, and is easily overwritten.
Object storage is an API over the filesystem that allows users to use a command on files (GET, PUT, DELETE) to a service, without worrying where they are actually stored. Its fundamental unit is an “object” — which is usually binary (images, sound files…).
The database is a persistent, fast, and scalable storage/retrieval of structured data. Its fundamental unit is a “row” (unique IDs, references to other rows, values in columns).
A data lake is the unstructured aggregation of data from multiple sources (databases, logs, expensive data transformations). It operates under the concept of “schema-on-read” by dumping everything in and then transforming the data for specific needs later.