Solid waste management (SWM) is critical for the sustainable development of the global economy and society, and it should involve the whole life cycle process of waste generation and treatment. Bibliometric and scientific knowledge mapping was applied in this study to systematically review 4239 published papers (1991–2022) in the Web of Science (WOS) core database to obtain an overview of the current knowledge network and the status of waste management research, as well as summarizing the hotspots and frontiers for future research. The results show that: (1) Since the 21st century, SWM research has received extensive attention. During the study period, the number of publications increasing from 7 to 552 per year over the course of the century. An important turning point was reached in 2015, which was followed by a rapid increase in the number of articles published, reaching a peak in 2021. (2) Well known universities in China and around the world were the main sites of knowledge generation, and the cooperative research networks between these institutions resulted in numerous publications. However, international cooperation in this field was still insufficient. (3) Solid waste management research is an interdisciplinary and diversified field, among which integrated waste management and environmental economic assessment, impact mechanisms and residents' behavior, and environmental change and sustainable development were the main research topics. (4) Solid waste management research could be organized into 30 clusters, which were further classified into initial, development, and leapfrog stages based on a timeline analysis of the literature co-citation network. Combining the keyword burst detection results and research hotspots, research frontiers were summarized for four periods, which could be used to describe the phase upgrade of SWM research. Finally, future research directions were proposed in terms of their perspectives, content, methods, and context, including SWM based on the "order-emotion" framework; consideration of multi-stakeholder games; adoption of new paradigms (e.g., machine learning and artificial intelligence); and consideration of social and environmental changes and externality costs to build a healthier and more sustainable integrated management system.