The low thermal conductivity of organic phase change materials degrades their power density and hinders access to their high energy density, which is available as latent heat. Porous foams with high thermal conductivity are often combined with organic phase change materials to increase effective thermal conductivity and hence, power density. However, volume constraints can lead to compromises in available energy density. On the other hand, the high thermal conductivity of metallic phase change materials often makes improving thermal conductivity unnecessary. However, metallic phase change materials may not be the best option under mass constraints due to their higher mass density. In this work, different types of porous foams were combined with an organic phase change material (pure eicosane): high-porosity copper foams (96 % porosity), sintered copper powder foam (55 % porosity), and graphite foam (72 % porosity). Pure gallium has also been considered as a potential metallic phase change material. Three different pore densities with comparable porosity were another feature of the highporosity copper foams. Depending on different conditions of heat rate (thermal boundary), thickness (geometry), and cutoff temperature, the results show the experimentally obtained transient thermal performance of eicosane and porous foam composites and compare them with a metallic phase change material (gallium). This research presents the experimental results and a novel framework that utilizes thermal Ragone plots. Using thermal Ragone plots, the study examines the performance of the phase change material composite in both melting and solidification cycles and highlights the effects of heat input, cutoff temperature, and aspect ratio on these processes. The analysis based on the thermal Ragone plots can provide important insights into the behavior of the composite material. The results are also displayed as volumetric and gravimetric thermal Ragone plots showing the power and energy densities to compare different cases under the volume and mass constraints.