Efficient In-Memory Inverted Indexes: Theory and Practice

Inverted indexes are the backbone of most large-scale information retrieval systems. Although conceptually simple, high-performance inverted indexes require a deep understanding of low-level system optimizations, compression techniques, and traversal strategies. With the widespread adoption of in-memory search engines, the rise of learned sparse retrieval (LSR), and the increasing complexity of ranking pipelines, the design space for efficient indexing and retrieval systems has expanded significantly.