Final answer:
Amazon S3 employs an eventual consistency model, which guarantees that updates to data, such as writes and deletions, will propagate and become consistent across all servers in time. Read-after-write consistency is provided for new objects, but eventual consistency applies for updates and deletions of objects.
Step-by-step explanation:
The data consistency model that Amazon S3 employs is called eventual consistency. This model is designed for distributed systems and ensures that if no new updates are made to a given data item, eventually, all accesses to that item will return the last updated value. Amazon S3 provides read-after-write consistency for PUTS of new objects in your S3 bucket in all regions with one caveat: if you make a HEAD or GET request to the key name (object) where the PUT is in process, or if the PUT request overwrites an existing object, you might get a 'NotFound' response.
For delete operations and PUTs of updates to existing objects, Amazon S3 provides eventual consistency. This means that it might take some time for all copies of an object to be updated across the distributed network. For example, if you delete an object and immediately attempt to read it, you may still retrieve the object for a brief period. However, the delete operation will propagate, and soon the object will no longer be accessible.