How to implement large-scale Poisson Regression in Python

I am trying to implement a Poisson Regression in Python to predict rates. I am dealing with a ton of data (too much to store in a DataFrame), which means that using the standard statsmodels.api GLM Poisson Regression won’t work. I know that sklearn has a partial_fit() method with the SGDRegressor and SGDClassifier classes for Minibatch learning, but I cannot figure out how to implement a Poisson Regression with these classes. Does anyone know how to implement a Poisson Regression with large-scale data in Python?