Unraveling the Web of Relationships: Understanding Graph Data
summary
Starts from the 1736 Seven Bridges problem and claims graph databases excel when relationships—not entities—drive value, especially for pattern matching, recommendations, fraud detection, geospatial routing and complex hierarchies. Covers practical SQL Server approaches (adjacency lists, path enumeration/hierarchyid, nested sets) and points out SQL Graph exists but Microsoft seems to have abandoned it. Introduces storage models (native vs multimodel), graph types (property vs RDF) and tools like Neo4j and TigerGraph, and stresses budget, talent and doing a proof of concept.
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chapters (13)
- 0:00Introduction
- 1:33Why graph data matters
- 2:36Graph theory history
- 3:39What is graph data
- 5:02Graph data applications
- 6:28Is your data graph-like
- 9:16Tools and budget for graphs
- 10:18Questions before graph adoption
- 11:41Graph algorithms in SQL Server
- 13:07What is a graph database
- 14:11Types of graph databases
- 15:56Graph query languages
- 16:38Relational vs graph differences
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