All databases scale the same way - by partitioning and sharding the dataspace. RDBMS have harder restrictions due to the features they provide and the performance expectations, but you can just as easily use a bunch of relational servers to partition a table (or several) across them by range or hashes of the primary key.
That's basically what key/value stores like DynamoDB do, and why DynamoDB was even built on MySQL (at least originally).
"can just as easily use a bunch of relational servers to partition a table" is not true at all. Managing, maintaining and tuning a sharded relational cluster is an astonishing amount of operations work. partition management, re-partioning, partition failover / promotions / demotions, query routing, shard discovery, upgrades... it goes on an on. All this work is gone if you pick dynamo.
Not saying that dynamo is always better, but IMHO people very much underestimate the ops cost of running a sharded relational cluster at scale.
That's basically what key/value stores like DynamoDB do, and why DynamoDB was even built on MySQL (at least originally).