The Parallel Data Assimilation Framework (PDAF) is a unified framework for ensemble data assimilation. PDAF has been developed to simplify the implementation of scalable ensemble data assimilation systems with existing high-dimensional numerical models. It provides support for the parallelization of the ensemble integration and fully implemented and parallelized ensemble Kalman and nonlinear filters. PDAF encapsulates the filter algorithms so that model and data assimilation developments can be conducted separately. I will review the structure and features of PDAF and discuss its use in different applications of ocean-biogeochemical and coupled atmosphere-ocean models.