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AI · April 8, 2026

Graphify AI

Turn any raw data into a graph database — in seconds

What it does

GraphifyAI converts CSV, Excel, Parquet, and SAS files into import scripts for Neo4j, Memgraph, Amazon Neptune, FalkorDB, and more — plus LangChain, LlamaIndex, LangGraph, and GraphRAG integration code. It infers nodes and relationships from your column structure automatically. No Cypher knowledge needed. Perfect for AI engineers building knowledge graphs and developers migrating relational data into graph databases. Supports 8 graph DBs and 4 AI FWs. No installation. Works in the browser.

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    Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…

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