In this work, we prove a small-time central limit theorem for the finite-dimensional distributions of sufficiently smooth transformations of solutions to stochastic Volterra integral equations X as well as its extension to a functional CLT, where we focus on locally square-integrable kernels K with small-time power law asymptotics and coefficients satisfying linear growth and Hölder conditions. Furthermore, we present two approaches for proving the non-Markovianity of certain SVIE solutions, which is of importance for applications in mathematical finance as it highlights the need for more sophisticated concepts for pricing and hedging financial derivatives. On the one hand, this can be achieved by reducing the SVIE via the above CLT to the Gaussian Riemann-Liouville case. Moreover, if K is also completely monotone, we can conclude the non-Markovianity of X by studying the conditional distributions of an appropriate, Hilbert space valued Markovian lift given X. We conclude by deriving a small-time CLT also for the Markovian lift, which implies the above CLT for X provided the applicability of a certain projection operator. Joint work with Martin Friesen and Stefan Gerhold.