  We investigate stochastic Volterra equations and their limiting laws. The
stochastic Volterra equations we consider are driven by a Hilbert space valued
\Levy noise and integration kernels may have non-linear dependence on the
current state of the process. Our method is based on an embedding into a
Hilbert space of functions which allows to represent the solution of the
Volterra equation as the boundary value of a solution to a stochastic partial
differential equation. We first gather abstract results and give more detailed
conditions in more specific function spaces.
