---
title: "Graph and Lakehouse, Friends at Last"
url: https://daily.dev/posts/graph-and-lakehouse-friends-at-last-yaocogzdk
source_url: https://medium.com/neo4j/graph-and-lakehouse-friends-at-last-getting-started-with-neo4j-virtual-graph-on-databricks-34554994a844
type: article
source: "neo4j"
published: 2026-06-22T22:20:38.096Z
updated: 2026-06-22T22:43:58.723Z
tags: ["architecture", "data-engineering", "databricks", "neo4j"]
reading_time: 19
upvotes: 0
comments: 0
language: en
---

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# Graph and Lakehouse, Friends at Last

**[neo4j](https://daily.dev/sources/neo4j)** · 19 min read · 0 upvotes · 0 comments

## Summary

Neo4j Virtual Graph is a new capability that overlays a property graph model on top of existing Databricks lakehouse data without moving it. Foreign keys and join tables become explicit, named relationships queryable via Cypher, which is then deterministically translated to SQL and executed on Databricks compute under Unity Catalog governance. The post walks through setting up Virtual Graph on the TPC-H benchmark dataset, covering schema preparation, composite key workarounds, data source connection, AI-assisted graph model generation, and several progressively complex Cypher query patterns — including star schema navigation, bipartite intersection, parametric lookups for agentic workflows, and multi-role supplier scoring — comparing each to its SQL equivalent to illustrate the semantic clarity gains.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/neo4j/graph-and-lakehouse-friends-at-last-getting-started-with-neo4j-virtual-graph-on-databricks-34554994a844>

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Tags: [#architecture](https://daily.dev/tags/architecture), [#data-engineering](https://daily.dev/tags/data-engineering), [#databricks](https://daily.dev/tags/databricks), [#neo4j](https://daily.dev/tags/neo4j)

[View this post on daily.dev](https://daily.dev/posts/graph-and-lakehouse-friends-at-last-yaocogzdk)
