Graph Databases: Talking about your Data Relationships with Python
summary
Shows when a graph store actually helps: relationships are first-class so traversal queries run faster while property scans do not, an academic benchmark finds. Demonstrates Neo4j, OrientDB, TitanDB and Python glue like py2neo, NetworkX, iGraph, with concrete Cypher and Python snippets that create nodes, edges, and run community and centrality algorithms. Presents two full analyses that ran end to end: a Brazil corruption network built from public expense and donation records and a Game of Thrones character graph, and cites 160 million Facebook users in Brazil as motivating scale.
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chapters (20)
- 0:00Introduction
- 1:30Who am I
- 4:10Presentation Outline
- 4:45Relationships
- 5:37Social Network
- 8:18Data Structure
- 8:50Visual Representation
- 10:06Graph Databases
- 10:23Advantages of Graph Databases
- 13:26New for J
- 13:40Most popular graph database
- 14:31Creating a node
- 16:44Creating a relationship
- 18:17Querying the data
- 19:44PyPipe to New York
- 23:45Querying with Graph Databases
- 27:05Applications
- 29:07Leonardo Salas
- 29:39Application
- 38:35Questions
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