A beta distribution has an approximate normal shape if its parameters are large, and so you could use normal approximations to compute beta inequalities. The corresponding normal inequalities can be computed in closed form.
This works surprisingly well. Even when the beta parameters are small and the normal approximation is a bad fit, the corresponding inequality approximation is pretty good.
For more details, see the tech report Fast approximation of beta inequalities.
Related post: Beta inequalities in R