![Cypher Query Language
● Interact with Neo4j
○ Add, delete, change, query data (SQL-inspired)
● Symbolic language
○ Node ()
○ Property {name:''Brett''}
○ Relationship <-- or -->
■ ()<--() or ()-->()
○ Label [:PERSON]](https://image.slidesharecdn.com/e95b53ce-2236-4b82-8c36-217c4780e3e7-151125233004-lva1-app6891/85/Brett-Ragozzine-Graph-Databases-and-Neo4j-10-320.jpg)
![Cypher Query Language
● Example
(brett:PERSON {name:''Brett''})-[:HAS_TITLE]->
(ds:TITLE {name:''Data Scientist''})
(brett)-[:WORKS_FOR {from:''April 2015''}]->
(cc:COMPANY {name:''CompuCom''})](https://image.slidesharecdn.com/e95b53ce-2236-4b82-8c36-217c4780e3e7-151125233004-lva1-app6891/85/Brett-Ragozzine-Graph-Databases-and-Neo4j-11-320.jpg)
![The End
● Thank you, and happy graphing!
(brett)-[:HAD_FUN]->(speaking)](https://image.slidesharecdn.com/e95b53ce-2236-4b82-8c36-217c4780e3e7-151125233004-lva1-app6891/85/Brett-Ragozzine-Graph-Databases-and-Neo4j-16-320.jpg)
Brett Ragozzine - Graph Databases and Neo4j
- 1. Graph Databases and Neo4j Brett Ragozzine, PhD Data Scientist Intermountain Big Data Conference Nov 21, 2015
- 3. Introduction ● PhD, Astrophysics ○ Dark matter, gravitational lensing, image analysis ● Data Scientist - CompuCom (remote, Dallas) ○ IT Outfitter, Service, Support ○ 1000 customers, millions of end-users ● Digital Innovation team ○ Neo4j
- 4. Outline ● Graph databases (NoSQL) ○ Why they’re different ○ What they do well ● Neo4j ● Cypher query language ● GraphGist examples ● Use cases ● Links for getting started
- 5. Graph Databases ● Great at storing: ○ Relationships (“first-class citizens”) ○ Properties ○ Sparse data, densely ● Relational DBs store all the 0s
- 6. Graph Databases ● Great for searching: ○ Subsets of the graph ● Great at finding: ○ Labeled data ○ Indexed data ■ relational DBs are too ○ Pattern matches ■ e.g. ''Friend-of-a-friend''
- 7. Graph Databases ● Nodes, relationships, properties, labels ○ Billions of nodes, relationships ● Properties ○ Don’t store too many together (slow) ○ Turn properties into nodes, where applicable ● Don’t store large files in a graph ○ Do store url
- 8. Graph Databases ● Schema ○ Design your graph around the your questions ■ Very different from relational DBs ○ Easy to re-design on the fly ■ Turn nodes into properties or vice versa ■ Difficult to do with relational DBs
- 9. Graph Databases ● Architecture ○ Single Master ■ Transactional (single write - pass/fail) ○ Large cluster ■ High availability (multiple queries/reads at once)
- 10. Cypher Query Language ● Interact with Neo4j ○ Add, delete, change, query data (SQL-inspired) ● Symbolic language ○ Node () ○ Property {name:''Brett''} ○ Relationship <-- or --> ■ ()<--() or ()-->() ○ Label [:PERSON]
- 11. Cypher Query Language ● Example (brett:PERSON {name:''Brett''})-[:HAS_TITLE]-> (ds:TITLE {name:''Data Scientist''}) (brett)-[:WORKS_FOR {from:''April 2015''}]-> (cc:COMPANY {name:''CompuCom''})
- 12. Examples: GraphGists ● Let’s go to the browser ● localhost:7474
- 13. How to Get Started ● Use cases ○ http://neo4j.com/use-cases/ ● Neo4j tutorial ○ http://neo4j.com/graphacademy/ ● GraphGists ○ http://graphgist.neo4j.com/#!/gists/all ○ https://github.com/neo4j-contrib/graphgist/wiki
- 14. How to Get Started ● Books
- 15. Other Graph Databases ● Top 5 Most Popular http://db-engines.com/en/ranking/graph+dbms (number of mentions, job postings, etc) ○ Neo4j ○ Titan ○ OrientDB ○ ArangoDB ○ Giraph
- 16. The End ● Thank you, and happy graphing! (brett)-[:HAD_FUN]->(speaking)