Percentage of smaller dataset with respect to bigger dataset
Naive approach: define a similarity or distance function, say for instance cosine similarity.

Calculate the similarity score between any pair $(x_i\in A, y_j\in B)$
Define a precision level, say $\epsilon=0.000001$. The assumption is that it's extremely unlikely that two vectors would be this close by chance in $A$.
For every $y_j\in B$, find the set $c(y_j) = \{ x_i\in A\ |\ sim(x_i,y_j)\geq 1-\epsilon \}$
Obtain the union: $C(B)=\{x_i\in A\ |\ \exists y_j\in B: x_i\in c(y_j) \}$

The proportion of elements of $A$ which are &quot;equal&quot; to an element in $B$ is:
$$\frac{|C(B)|}{|A|}$$