  We prove an equivalence between open questions about the embeddability of the
space of persistence diagrams and the space of probability distributions
(i.e.~Wasserstein space). It is known that for many natural metrics, no coarse
embedding of either of these two spaces into Hilbert space exists. Some cases
remain open, however. In particular, whether coarse embeddings exist with
respect to the $p$-Wasserstein distance for $1\leq p\leq 2$ remains an open
question for the space of persistence diagrams and for Wasserstein space on the
plane. In this paper, we show that embeddability for persistence diagrams
\redd{is equivalent to} embeddability for Wasserstein space on $\mathbb{R}^2$.
\redd{When $p > 1$, Wasserstein space on $\mathbb{R}^2$ is snowflake universal
(an obstruction to embeddability into any Banach space of non-trivial type) if
and only if the space of persistence diagrams is snowflake universal.
