This answer isn't going to be fun, but I'm going to be pedantic here to justify why it's okay to ignore constants in big-$O$ by using the formal definition.
Definition: Let $f$ and $g$ be functions that map from $\mathbb{N}$ to $\mathbb{N}$. We say that $f \in O(g)$ ("$f$ is in big-$O$ of $g$") iff: $\exists k \in \mathbb{N}, \exists n_0 \in \mathbb{N}, \forall n \in \mathbb{N}, \left[n > n_0 \Rightarrow f(n) < k \cdot g(n)\right]$.
In English, that says there exists a constant $k$ and a constant $n_0$ such that every $n$ greater than $n_0$ will imply that $f(n) < k \cdot g(n)$. The constant $k$ controls how much to scale the function $g$, and the constant $n_0$ controls how many small numbers to ignore.
We know from the change-of-base formula that $\displaystyle\log_b a = \frac{\ln a}{\ln b}$.
Claim: For any $a, b > 1$, we have that $f \in O(\log_a n)$ if and only if $f \in O(\log_b n)$.
Given on the left side that $f \in O(\log_a n)$, we know that there must exist constants $k$ and $n_0$ to satisfy the big-$O$ definition. To make it satisfy the definition for $f \in O(\log_b n)$ on the right side, we take $k' = k \frac{\ln b}{\ln a}$ and the same $n_0$, and the formula will work out.
In conclusion, it is redundant for big-$O$ purposes to write the base of the logarithm as long as it greater than one. So writing a vague-looking $f \in O(\log n)$ loses no information.