Welcome SQL2Graph + Unstructured2Graph: Your New RAG Tools in Memgraph’s AI Toolkit
Blog post from Memgraph
Context engineering has emerged as a critical challenge for AI teams, with the difficulty lying in structuring, retrieving, and reasoning over data rather than in the large language models themselves. Memgraph's AI Toolkit, including SQL2Graph and Unstructured2Graph, addresses this by simplifying the transformation of structured and unstructured data into graph-ready formats, enabling efficient data conversion for Graph-based Retrieval-Augmented Generation (GraphRAG). SQL2Graph converts SQL schemas from relational databases like MySQL and PostgreSQL into graph models with the help of the Hypothetical Graph Model (HyGM), allowing for either automatic or incremental migration. Unstructured2Graph turns unstructured documents into connected knowledge graphs, integrating tools like LightRAG for LLM-based entity extraction. These innovations aim to facilitate AI engineers and data scientists in building intelligent systems by providing a seamless transition of data into graph domains, paving the way for future collaborative environments through the upcoming MCP Client in Memgraph Lab.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 3 | 5,556 | 752 | 184 | +14% |
| MCP | 3 | 3,335 | 319 | 128 | -31% |
| RAG | 3 | 1,128 | 182 | 76 | +4% |
| Data Pipeline | 1 | 336 | 120 | 61 | -36% |
| Multi-agent systems | 1 | 261 | 87 | 52 | +14% |
| Real-time | 1 | 4,542 | 1,005 | 235 | -31% |
| Vector Search | 1 | 1,303 | 288 | 128 | -18% |
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