Point cloud streaming is a key component of 5G (and beyond) networks, serving as a foundation for holographic communication. While it enables immersive experiences, it also poses significant challenges to network infrastructure. Uncompressed point cloud streams produce Gbps traffic volumes, while compressed streams often suffer from multi-second latencies. Therefore, the feasibility of real-time applications that require ultra-low motion-to-eye latency, such as Network Music Performance and Remote Driving, remains unclear. In this work, we design and implement a novel point cloud streaming tool, based on the Draco encoder, Intel’s RealSense SDK, and OpenGL. We deploy our prototype implementation in a private 5G stand alone network and provide an in-depth analysis of the latency and throughput of point cloud streaming. Our results show that deploying volumetric streaming services over 5G networks is still a challenging task. However, a combination of simple cost-reduction strategies can bring it significantly closer to feasibility.