Hybrid Retrieval-Augmented Generation on Serverless PostgreSQL: A Comparative Evaluation of HyDE, Graph-Based, and Fusion Retrieval Strategies

We present a lightweight RAG architecture built entirely on PostgreSQL with pgvector and serverless edge functions, implementing and evaluating four retrieval strategies: hybrid search with Reciprocal Rank Fusion (RRF), Hypothetical Document Embeddings (HyDE), multi-query expansion, and graph-based retrieval over an automatically constructed knowledge graph. Evaluation on a 427-document Spanish-language corpus with 22 ground-truth pairs shows HyDE with the strongest point estimates (P@5: 0.595, MRR: 0.838, Hit Rate: 1.0). Because the ground-truth set is small (n=22) and no confidence intervals or significance tests are reported, these comparisons should be read as exploratory, and the Hybrid (RRF) and Graph-Based figures used for comparison are themselves preliminary estimates pending full cross-validated runs.Editorial revision. The prose was converted to an impersonal, formal register (single-author paper). No data, numbers, claims, tables, or references were changed from the previous version.