This survey provides a comprehensive overview of 3D Gaussian Splatting (3DGS), analyzing its technologies, applications, challenges, and opportunities. 3DGS is a promising technique for 3D representation, capable of transforming multi-view images into explicit 3D Gaussian representations and achieving real-time rendering of novel views. The survey discusses the optimization, application, and extension of 3DGS, categorizing them based on their focuses or motivations. It summarizes and classifies nine types of technical modules and corresponding improvements identified in existing works. The survey also examines the common challenges and technologies across various tasks, proposing potential research opportunities. The survey highlights the efficiency and controllable explicit representation of 3DGS, which makes it applicable across a diverse array of fields, including virtual reality, robotics, film, and urban planning. The survey also discusses the challenges of generalization and sparse view settings, and proposes solutions to address these challenges. The survey provides an overview of the applications of 3DGS, including human reconstruction, artificial intelligence-generated content (AIGC), and autonomous driving. The survey also discusses the challenges of real-time rendering and photorealism, and proposes solutions to address these challenges. The survey concludes with a discussion of the future research directions for 3DGS.This survey provides a comprehensive overview of 3D Gaussian Splatting (3DGS), analyzing its technologies, applications, challenges, and opportunities. 3DGS is a promising technique for 3D representation, capable of transforming multi-view images into explicit 3D Gaussian representations and achieving real-time rendering of novel views. The survey discusses the optimization, application, and extension of 3DGS, categorizing them based on their focuses or motivations. It summarizes and classifies nine types of technical modules and corresponding improvements identified in existing works. The survey also examines the common challenges and technologies across various tasks, proposing potential research opportunities. The survey highlights the efficiency and controllable explicit representation of 3DGS, which makes it applicable across a diverse array of fields, including virtual reality, robotics, film, and urban planning. The survey also discusses the challenges of generalization and sparse view settings, and proposes solutions to address these challenges. The survey provides an overview of the applications of 3DGS, including human reconstruction, artificial intelligence-generated content (AIGC), and autonomous driving. The survey also discusses the challenges of real-time rendering and photorealism, and proposes solutions to address these challenges. The survey concludes with a discussion of the future research directions for 3DGS.