This survey provides a comprehensive overview of compression and compaction techniques for 3D Gaussian Splatting (3DGS), a state-of-the-art method for real-time radiance field rendering. 3DGS represents scenes as a collection of 3D Gaussians, offering high quality and speed. However, its high storage and memory demands limit its practicality for mobile and VR devices. This survey evaluates various compression and compaction methods, aiming to reduce file size and Gaussian count while maintaining or improving quality. The survey classifies methods into compression (reducing file size) and compaction (reducing Gaussian count), and discusses their respective advantages and disadvantages. The survey also introduces key mathematical concepts and implementation details, and provides a consistent framework for comparing the surveyed methods. The survey highlights the importance of compression for 3DGS, as it enables faster transmission, rendering on lower-end devices, and the creation of larger, more complex scenes. The survey also discusses various compression techniques, including vector quantization, octrees, anchor-based representations, hash-grids, Z-order curves, tri-planes, and self-organizing Gaussians. The survey also discusses attribute pruning and compaction techniques, which aim to reduce the number of Gaussians while maintaining visual quality. The survey concludes that a combination of compression and compaction techniques is necessary to achieve efficient 3DGS representations. The survey provides a detailed analysis of various compression and compaction methods, and highlights the importance of these techniques for the practical application of 3DGS.This survey provides a comprehensive overview of compression and compaction techniques for 3D Gaussian Splatting (3DGS), a state-of-the-art method for real-time radiance field rendering. 3DGS represents scenes as a collection of 3D Gaussians, offering high quality and speed. However, its high storage and memory demands limit its practicality for mobile and VR devices. This survey evaluates various compression and compaction methods, aiming to reduce file size and Gaussian count while maintaining or improving quality. The survey classifies methods into compression (reducing file size) and compaction (reducing Gaussian count), and discusses their respective advantages and disadvantages. The survey also introduces key mathematical concepts and implementation details, and provides a consistent framework for comparing the surveyed methods. The survey highlights the importance of compression for 3DGS, as it enables faster transmission, rendering on lower-end devices, and the creation of larger, more complex scenes. The survey also discusses various compression techniques, including vector quantization, octrees, anchor-based representations, hash-grids, Z-order curves, tri-planes, and self-organizing Gaussians. The survey also discusses attribute pruning and compaction techniques, which aim to reduce the number of Gaussians while maintaining visual quality. The survey concludes that a combination of compression and compaction techniques is necessary to achieve efficient 3DGS representations. The survey provides a detailed analysis of various compression and compaction methods, and highlights the importance of these techniques for the practical application of 3DGS.