A Comparative Analysis of Standard and Graph-Based Retrieval-Augmented Generation

Abstract

This study investigates the performance of Retrieval-Augmented Generation (RAG) systems, comparing a standard implementation with a graph-driven approach. The paper details the architectural differences between the two systems and presents a comprehensive evaluation of their performance on a diverse dataset. The results demonstrate the advantages of using knowledge graphs to capture relationships between entities, particularly for complex queries. The analysis also considers the trade-offs between performance and resource consumption, providing insights into the practical applications of each approach.