GraphDB
Download as PPTX, PDF0 likes828 views
This document discusses graph databases and the graph database Neo4j. It provides an introduction to NoSQL databases and graph theory, including graph algorithms. It outlines some common uses of graph databases such as social networking, recommendations, and identity and access management. It also provides examples of Cypher queries that can be used with Neo4j to find and create nodes and relationships.
![Neo4j
Creating relation for existing node
MATCH (me : Person {name = “Omer”})
CREATE (me)-[:FRIEND]->(friend : Person {name = “Seda”})
Cypher](https://image.slidesharecdn.com/graphdb-150516025508-lva1-app6892/85/GraphDB-29-320.jpg)
![Neo4j
Fetching friends of me
MATCH (me : Person {name = “Omer”})-[:FRIEND]->(friend : Person)
RETURN me, friend;
Cypher](https://image.slidesharecdn.com/graphdb-150516025508-lva1-app6892/85/GraphDB-30-320.jpg)
![Neo4j
Fetching friends of friends of fiends of me
MATCH (me : Person {name = “Omer”})-[f1:FRIEND] -[f2:FRIEND] -[f3:FRIEND]->(f4:
Person)
RETURN me, f1, f2, f3, f4;
Cypher](https://image.slidesharecdn.com/graphdb-150516025508-lva1-app6892/85/GraphDB-31-320.jpg)
GraphDB
- 1. Internet Programming II Yildiz Technical University 2015 Graph Databases { "name” : "Omer Taskin", "company” : "eBay Inc.", "title” : "Software Engineer" }
- 4. Data is getting bigger day by day
- 5. Database is a thing where data is kept and managed!
- 6. Database is a thing where data is kept and managed! files are databases too
- 7. Relational Database(s) RDBMS supports JOIN(s) between tables invented @IBM in 1970
- 8. •SQL became a standard; –American National Standards Institute (ANSI) in 1986 –International Organization for Standardization (ISO) in 1987
- 10. Relational Database(s) RDBMS Every table has to be in a schema Data has to be stored into table(s)
- 11. NoSQL •means Not Only SQL •Started to use in 2009 @ last.fm •A Database Management System •Non-relational! •No Joins! •Mostly non-transactional
- 13. Graph Theory History Seven bridges of Königsberg (Germany) Found @in 1736
- 14. Graph Theory Node Edge And Property Graphs usually are not small like that
- 16. Graph Theory GraphDB vs RDBMS fetching by Join Graph database
- 22. Network and IT Operations Management The interconnected physical, virtual, and application layers of a network are perfectly modeled in a comprehensive graph. Queries: Quality-of-Service Mapping, Impact Analysis, Root Cause Analysis, Asset Management Graph Databases Use Cases
- 23. Social Family, friends and followers extend into a social graph which reveals patterns of similar behavior, influence, and implicit groups. Queries: Friend Recommendations, Sharing & Collaboration, Influencer Analysis Graph Databases Use Cases
- 24. Recommendations Connect the dots of seemingly unrelated interests and relationships to make recommendations that balance fresh with familiar. Queries : Professional Recommendations Product, Social, Service Graph Databases Use Cases
- 25. Identity and Access Management Who you are, how you belong, and what you’re permitted depends upon the relationships between you, an organization, and a system. Queries : Interconnected Group Organization, Access Management, Provenance Graph Databases Use Cases
- 26. Graph Databases Most popular graph database Open source Implemented in Java Neo4j
- 27. Neo4j Cypher is query language of Neo4j Cypher
- 28. Neo4j Finding nodes MATCH (node : Person) RETURN node Creating node CREATE (person : Person {name = “Omer”}) Cypher
- 29. Neo4j Creating relation for existing node MATCH (me : Person {name = “Omer”}) CREATE (me)-[:FRIEND]->(friend : Person {name = “Seda”}) Cypher
- 30. Neo4j Fetching friends of me MATCH (me : Person {name = “Omer”})-[:FRIEND]->(friend : Person) RETURN me, friend; Cypher
- 31. Neo4j Fetching friends of friends of fiends of me MATCH (me : Person {name = “Omer”})-[f1:FRIEND] -[f2:FRIEND] -[f3:FRIEND]->(f4: Person) RETURN me, f1, f2, f3, f4; Cypher