Graph Databases + Neo4j

A primer on graph databases, why you would use one, what they do, and one application for a graph database.

Transcript

1. Graph Databases & Neo4j Regina Imhoff @StabbyMcDuck
2. What is a graph?
3. Charles Annie Betty Follows Follow s Follow s Follows
4. Charles Annie Betty Follows Follow s Follow s Follows Node (Vertex)
5. Charles Annie Betty Follows Follow s Follow s Follows Node (Vertex) Relationship (Edge)
6. Graph Databases • CRUD • Create, Read, Update, Delete • Non-Relational (NoSQL) • Connected data • Social networks!
7. Property Graph • Nodes • Contain properties (key-value pairs) • One or more labels • Relationships • Named • Directional • Can also contain properties
8. Graph Storage • Storage • Native graph storage: optimized for storing and managing graphs • Non-native: serialize into relational, object-oriented, or other data store
9. Graph Processing • Native graph processing: leverage index-free adjacency • Connected nodes physically point to each other • Relationships are turned into first class entities in data records at store level • Non-native graph processing: place a layer of graph on an existing database storage engine • Can’t do graph traversal as it isn’t stored as a graph
10. Why Use a Graph Database? • Performance • Increased performance when working with connected data • Join-intensive query performance • Relational databases deteriorate • Graph databases remain mostly constant • Queries are localized to a portion of the graph • Even as data set gets bigger!
11. Why Use a Graph Database? • Flexibility • Graph databases are additive • Can add new kinds of relationships, nodes, labels, subgraphs, etc. to existing structure • Won't disturb existing queries! • Less developer time spent on modeling domains
12. Why Use a Graph Database? • Agility • Schema-free • Change the data model as you develop
13. IRL Scenario • The manufacturing and sales of yarn • Applicable to most social and manufacturing! • www.ravelry.com
14. IRL Scenario
15. Wool Cards Material User Carding
16. Wool Cards Material User Carding Owns User Owns User
17. Carding Material Dyeing User Dyes
18. Dyeing Spins Material Material Spinning User Carding Material
19. Material Knits Item User Spinning Patterns Authors Pattern User
20. Wool Carding User Cards Material Dyeing Material User Dyes Spinni ng Material Material User Spins Material Item Material User Knits Pattern Patterns User Authors User Owns
21. Owns Initiates Exchanged User Item Transaction Transactions
22. Owned Owns Receives Owns Initiates Exchanged User Item Transaction User Transactions
23. ☠ RUT-ROH! ☠ • Scenario: somebody who purchased a skein of yarn has tested positive for anthrax! • We need to find all the people who were involved in the production of this dye lot to test them too
24. SQL Query // Spinner SELECT users.* FROM users INNER JOIN spinnings ON spinnings.spinner_id = users.id INNER JOIN items ON items.material_id = spinnings.id INNER JOIN users as knitters ON knitters.id = items.knitter_id WHERE knitters.name = "Bob" UNION
25. SQL Query // Dyer SELECT users.* FROM users INNER JOIN dyeings ON dyeings.dyer_id = users.id INNER JOIN spinnings ON spinnings.material_id = dyeings.id INNER JOIN items ON items.material_id = spinnings.id INNER JOIN users as knitters ON knitters.id = items.knitter_id WHERE knitters.name = "Bob" UNION
26. SQL Query // Carder SELECT users.* FROM users INNER JOIN cardings ON cardings.carder_id = users.id INNER JOIN dyeings ON dyeings.material_id = cardings.id INNER JOIN spinnings ON spinnings.material_id = dyeings.id INNER JOIN items ON items.material_id = spinnings.id INNER JOIN users as knitters ON knitters.id = items.knitter_id WHERE knitters.name = "Bob"
27. Cypher Query MATCH (p:Person)-[:OWNS]->(i:Item)-[*]-(q:Person) WHERE p.name = ‘Bob' AND i.name = 'socks' RETURN q
28. Cypher Query MATCH (p:Person)-[:OWNS]->(i:Item)-[*]-(q:Person) WHERE p.name = ‘Bob' AND i.name = 'socks' RETURN q Variable
29. Cypher Query MATCH (p:Person)-[:OWNS]->(i:Item)-[*]-(q:Person) WHERE p.name = ‘Bob' AND i.name = 'socks' RETURN q Variable Node
30. Cypher Query MATCH (p:Person)-[:OWNS]->(i:Item)-[*]-(q:Person) WHERE p.name = ‘Bob' AND i.name = 'socks' RETURN q Variable Node Relationship
31. Cypher Query MATCH (p:Person)-[:OWNS]->(i:Item)-[*]-(q:Person) WHERE p.name = ‘Bob' AND i.name = 'socks' RETURN q Variable Node Relationship Variable length path
32. Cypher Query MATCH (p:Person)-[:OWNS]->(i:Item)-[*]-(q:Person) WHERE p.name = ‘Bob' AND i.name = 'socks' RETURN q Variable Node Relationship Variable length path Type
33. Cypher Query MATCH (p:Person)-[:OWNS]->(i:Item)-[*]-(q:Person) WHERE p.name = ‘Bob' AND i.name = 'socks' RETURN q Variable Node Relationship Variable length path Type Directed Relationship Relationship
34. Cypher Query
35. Cypher Query
36. Cypher Query
37. Neo4j Browser