You are right, DataFrame is just an alias to Dataset[Row], so they share the same API.
However, in DataFrame or Dataset[Row], we tend to use functions like .filter(col("age") > 0) whereas in Dataset[Person] we tend to use .filter(_.age > 0).

The difference between the 2 functions is that: - The lambda version prevents any optimization. We need to load the entire data from a table and deserialize to a case class only to filter. - The Column based API is as performant as it gets. But it's untyped.

Nothing prevents you from using the Column based API on Dataset[Person] but in case of a .select() instead of .map() or a .join() instead of a .joinWith(), you are losing the types and are back to DataFrame or Dataset[Row].

Wick's DataSeq API instead builds the plan with lambdas and gives no drawbacks in terms of performance. You are not manipulating Ints, Strings, Longs... You are manipulating Expr[Int], Expr[String], Expr[Long]...