From SQL to Knowledge Graphs: An LLM-Driven Multi-Agent Approach with Data Schema Improvement
RDBMS (Relational Database Management System) databases face several limitations, including slow execution with multi-hop queries and a lack of explainability by graphical interpretations. In contrast, Graph database offers a more intuitive and efficient data schema that performs faster execution on large datasets. Most existing RDBMS conversion pipelines focus on running traditional loading commands and relying on Cypher queries. However, the efficiency of using an LLM to generate an effective graph data schema, significantly reducing the ambiguity of the graph database, remains underexplored in the current research literature. This paper presents a novel algorithm that bridges RDBMS and...
| Authors | Dinh-Khanh Pham, Quy-Anh Dang, Lam Mai Thanh et al. |
|---|---|
| Primary category | cs.DB |
| Published | 17 June 2026 |
| Last updated at source | 17 June 2026 |
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