RISE: A Rust Library for Inverted Index Search Engines

2026-06-05

AI Summary

This work addresses the challenge of efficiently constructing and querying inverted indexes over large-scale text corpora by designing and implementing a high-performance, memory-safe, and scalable inverted index library in Rust. Leveraging Rust’s zero-cost abstractions, concurrency safety guarantees, and expressive trait-based generics, the system flexibly integrates multiple classical inverted indexing techniques and supports efficient full-text retrieval algorithms. Experimental evaluation across several standard datasets and query workloads demonstrates that the proposed library achieves up to twice the query performance of state-of-the-art alternatives, substantially enhancing both retrieval efficiency and practical applicability.

Abstract

Inverted indexes are a crucial data structure for efficient information retrieval in large text corpora. They enable fast full-text search by mapping each term to the documents in which it appears, on top of which efficient algorithms quickly retrieve the documents relevant to a user query. We present RISE, a novel inverted index library implemented in Rust, designed to deliver high performance and efficiency for information retrieval tasks. RISE leverages Rust's safety and performance to provide a robust solution for building and querying inverted indexes, while offering accessible extensibility through its expressive trait system. While developing RISE, we revisited the inverted-index literature, thereby reproducing numerous prior works using this new test bench. We evaluated RISE against existing libraries, demonstrating competitive query performance across various datasets and workloads, with speedups of up to 2x over the current state of the art. Our results indicate that RISE is a promising tool for researchers and practitioners in the field of information retrieval.

Problem

• inverted index
• information retrieval
• performance
• efficiency
• large text corpora

Innovation

• inverted index
• Rust
• information retrieval
• high performance
• extensibility