Evolution of Buffer Management in Database Systems: From Classical Algorithms to Machine Learning and Disaggregated Memory

TL;DR

This survey reviews four decades of buffer management research, highlighting the evolution from classical algorithms to modern machine learning techniques and disaggregated memory architectures, and discusses future research directions.

Contribution

It provides a comprehensive analysis of buffer management evolution, integrating historical algorithms, system implementations, and emerging trends in heterogeneous memory management.

Findings

Classical algorithms like LRU-K, 2Q, LIRS, and ARC have shaped buffer management.

Emerging trends include machine learning-augmented policies and disaggregated memory architectures.

Open challenges involve integrating cross-layer approaches for heterogeneous memory hierarchies.

Abstract

Buffer management remains a critical component of database and operating system performance, serving as the primary mechanism for bridging the persistent latency gap between CPU processing speeds and storage access times. This paper provides a comprehensive survey of buffer management evolution spanning four decades of research. We systematically analyze the progression from foundational algorithms like LRU-K, 2Q, LIRS, and ARC to contemporary machine learning-augmented policies and disaggregated memory architectures. Our survey examines the historical OS-DBMS architectural divergence, production system implementations in PostgreSQL, Oracle, and Linux, and emerging trends including eBPF-based kernel extensibility, NVM-aware tiering strategies, and RDMA-enabled memory disaggregation. Through analysis of over 50 seminal papers from leading conferences (SIGMOD, VLDB, OSDI, FAST), we identify key architectural patterns, performance trade-offs, and open research challenges. We conclude by outlining a research direction that integrates machine learning with kernel extensibility mechanisms to enable adaptive, cross-layer buffer management for heterogeneous memory hierarchies in modern database systems.