"Small" means 1MiB per record here. But a higher level abstraction could split one logical operation into multiple records. Just like FoundationDB has severe limits on its transaction size, while higher level databases built on top of it work around that limit.
This product offers two advantages over S3: 1) Appending a small amount of data is cheap 2) Writes are forced into a consistent order (so you don't need to implement Paxos or RAFT yourself). Neither of these are useful for backups. Raw S3 already works well for that usage-case, especially now that Amazon added support for pre-conditions.
The OP's blog post linked to this article, which explains some scenarios where this storage primitive would be helpful: https://engineering.linkedin.com/distributed-systems/log-wha...
This product offers two advantages over S3: 1) Appending a small amount of data is cheap 2) Writes are forced into a consistent order (so you don't need to implement Paxos or RAFT yourself). Neither of these are useful for backups. Raw S3 already works well for that usage-case, especially now that Amazon added support for pre-conditions.