3D point clouds are increasingly used in applications, such as 3D remapping, cultural heritage preservation, and virtual/augmented reality. Given their large data volume, efficient compression is crucial. The MPEG group has introduced two standards: Geometry-based Point Cloud Compression (G-PCC), for static and dynamic-acquired point clouds, and Video-based Point Cloud Compression (V-PCC), specifically for dynamic point clouds. Although both approaches achieve effective data reduction, their high computational complexity limits real-time use, especially on resource-constrained devices. This paper analyzes the computational cost and coding efficiency of G-PCC and V-PCC, identifying the most time-consuming steps. In G-PCC, the Octree-RAHT configuration offers the best trade-off between efficiency and encoding time, with recoloring alone accounting for up to 70%. In V-PCC, video encoding dominates, consuming about 92% of the total time. These findings lay the groundwork for future optimizations to reduce the complexity of more efficient implementations.