As is often the case, the problem as stated is massively underspecified. -----I know, sorry...-----


For instance:
- Are your target addresses are correlated, perhaps even strictly sequential (in which case the solution is trivial)? -----no link between the addresses -----
- How large is the dataset; -----2^69 - 2^70 addresses-----    is it feasible to transfer it to several kernels for parallellisation? -----no idea, perhaps.-----
- Is the dataset mutable, or is it feasible to perform an initial, heavy transformation (in which case perfect hashing might outperform probabilistic/Bloom)?  -----It is a random dataset of around 2^70 addresses specifically created so that only a few of them have small keys in range 2^40-2^41. The files are not yet created due to the lack of knowledge on how to create a dataset that would work with tools such as bitCrack, etc...But essentially the task at hand will be to find those small range keys while searching the huge dataset mentioned... -----

Et cetera. A general database engine is almost certainly not optimal in either case.----- rather than optimal my question hints at ...is this even possible? -----