Survey on Memory-Disaggregated Indexing Systems

Disaggregated memory (DM), as an emerging hardware architecture, has attracted extensive attention from both academia and industry in recent years. This architecture physically decouples computing and memory resources in data centers and interconnects them via high-speed networks, thereby improving resource utilization, system elasticity, and fault isolation capabilities. Distributed indexes, as the core component of memory-disaggregated storage systems, play a crucial role in efficiently organizing and maintaining data to support high-throughput, low-latency data access. However, due to the inherent resource constraints of DM, fully exploiting the benefits of resource disaggregation to maximize index performance remains challenging. A comprehensive survey of the research progress on memory-disaggregated indexing systems is presented. First, the fundamental features of DM and remote direct memory access (RDMA) are introduced, and the primary challenges in constructing high-performance indexes on DM are identified: concurrency control, read and write amplifications, and caching overhead. Subsequently, existing indexing systems are categorized into three types based on their underlying data structures: hash indexes, tree indexes, and hybrid indexes. Representative systems in each category are analyzed to illustrate their design principles, implementation challenges, and key techniques. Finally, the main issues that require focused investigation in future research are highlighted, including cross-node cooperation, fault tolerance mechanisms, and adaptation to emerging software and hardware.