Webinar
From Tables to Knowledge Graphs: SQL2Graph for GraphRAG
Most enterprise context still lives in SQL tables, but GraphRAG needs connected structure to answer multi-hop, explainable questions. In this live technical session, we walked through how the Memgraph AI Toolkit helps you turn relational schemas into production-ready knowledge graphs using SQL2Graph agentic migration tool powered by HyGM (Hypothetical Graph Model).
You’ll see how SQL2Graph interprets PK/FK relationships, handles wide tables and junction patterns, and builds a graph with clear provenance. We’ll also look at how HyGM proposes, explains, and iteratively refines a graph model from your schema so you can validate assumptions before migrating to Memgraph.
What You’ll Learn
You’ll see how SQL2Graph interprets PK/FK relationships, handles wide tables and junction patterns, and builds a graph with clear provenance. We’ll also look at how HyGM proposes, explains, and iteratively refines a graph model from your schema so you can validate assumptions before migrating to Memgraph.
What You’ll Learn
- Why GraphRAG needs structured context (not just embeddings)
- How HyGM proposes, explains, refines, and validates a graph model from your SQL schema.
- How SQL2Graph translates relational patterns into a clean graph structure.
