Earlier quoted context omitted.
I'll second what Chubot said that I'm not liking the SQL much. The interface I'd like would be something close to numpy (or matlab/r, if those are more familiar). Let me do vectorized operations and write functions in code. Let me load a few different timeseries into a dataframe. Most likely the easiest thing to do would just be to either embed numpy into your engine, or create simple wrappers to load data to it.
The numpy style interface might be interesting. The problem is that it would probably kill performance to marshal into a Python process. Unless there's some way to embed numpy? Supporting custom functions is definitely something we want to do.
Why would it kill performance? All you need to do is this:
double* values = (double*)malloc(sizeof(double)*num_of_values);