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![Make two nodes
CREATE (:person {id: 1, name: “Kisung Kim”, birthday: 1980-01-05});
CREATE (:company {id: 1, name: “Bitnine Global”});
Make a relationship between the two nodes
MATCH (p:person {id: 1}), (c:company {id:1})
CREATE (p)-[:workFor {title: “CTO”, since: 2014}]->(c);
Kisung Kim Bitnine Global
workFor](https://image.slidesharecdn.com/pgconfsv2016-implementinggraphdatabasebased-onpostgresql-161122001733/75/Pg-Conf-Implementing-Graph-Database-based-on-PostgreSQL-7-2048.jpg)
![Querying
MATCH (p:person {name: “Kisung Kim”})-[:workFor]->(c:company)
RETURN (p), (c)
No Table Definitions and No Joins
Query with variable length relationships
MATCH (p:person {name: “Kisung Kim”})-[:knows*..3]->(f:person)
RETURN (f)
Kisung Kim ?
workFor
Kisung Kim ?
knows
?
knows
?
knows](https://image.slidesharecdn.com/pgconfsv2016-implementinggraphdatabasebased-onpostgresql-161122001733/75/Pg-Conf-Implementing-Graph-Database-based-on-PostgreSQL-8-2048.jpg)
![•
•
•
•
( ) -[:processes]->(Cypher)](https://image.slidesharecdn.com/pgconfsv2016-implementinggraphdatabasebased-onpostgresql-161122001733/75/Pg-Conf-Implementing-Graph-Database-based-on-PostgreSQL-11-2048.jpg)
![Make two nodes
CREATE (:person {id: 1, name: “Kisung Kim”, birthday: 1980-01-05});
CREATE (:company {id: 1, name: “Bitnine Global”});
Make a relationship between the two nodes
MATCH (p:person {id: 1}), (c:company {id:1})
CREATE (p)-[:workFor {title: “CTO”, since: 2014}]->(c);
Kisung Kim Bitnine Global
workFor](https://crownmelresort.com/image.slidesharecdn.com/pgconfsv2016-implementinggraphdatabasebased-onpostgresql-161122001733/75/Pg-Conf-Implementing-Graph-Database-based-on-PostgreSQL-7-2048.jpg)
![Querying
MATCH (p:person {name: “Kisung Kim”})-[:workFor]->(c:company)
RETURN (p), (c)
No Table Definitions and No Joins
Query with variable length relationships
MATCH (p:person {name: “Kisung Kim”})-[:knows*..3]->(f:person)
RETURN (f)
Kisung Kim ?
workFor
Kisung Kim ?
knows
?
knows
?
knows](https://crownmelresort.com/image.slidesharecdn.com/pgconfsv2016-implementinggraphdatabasebased-onpostgresql-161122001733/75/Pg-Conf-Implementing-Graph-Database-based-on-PostgreSQL-8-2048.jpg)
![•
•
•
•
( ) -[:processes]->(Cypher)](https://crownmelresort.com/image.slidesharecdn.com/pgconfsv2016-implementinggraphdatabasebased-onpostgresql-161122001733/75/Pg-Conf-Implementing-Graph-Database-based-on-PostgreSQL-11-2048.jpg)
Uploaded byJoshua Bae
Pg Conf - Implementing Graph Database based-on PostgreSQL
This document summarizes key differences between relational and graph databases, how to model and query graph data using Neo4j, and provides an overview of popular graph database solutions including Neo4j, Titan, and AgensGraph. Relational databases use tables and rows to represent entities and relationships, while graph databases use nodes and edges. Graph queries can traverse relationships in variable lengths and have no concept of tables or joins.
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Pg Conf - Implementing Graph Database based-on PostgreSQL
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- 4. • • Relational Database GraphDatabase Entity Row Node (Vertex) Relationship Row Relationship (Edge)
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- 7. Make two nodes CREATE(:person {id: 1, name: “Kisung Kim”, birthday: 1980-01-05}); CREATE (:company {id: 1, name: “Bitnine Global”}); Make a relationship between the two nodes MATCH (p:person {id: 1}), (c:company {id:1}) CREATE (p)-[:workFor {title: “CTO”, since: 2014}]->(c); Kisung Kim Bitnine Global workFor
- 8. Querying MATCH (p:person {name:“Kisung Kim”})-[:workFor]->(c:company) RETURN (p), (c) No Table Definitions and No Joins Query with variable length relationships MATCH (p:person {name: “Kisung Kim”})-[:knows*..3]->(f:person) RETURN (f) Kisung Kim ? workFor Kisung Kim ? knows ? knows ? knows
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- 10. Magic Quadrant forOperational Database Management Systems, Gartner, 2016
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- 15. Solution Company LatestVersion Features Neo Technology 3.1 Most famous graph database, Cypher O(1) access using fixed-size array Datastax - Distributed graph system based on Cassandra Titan
- 16. • • • • From Graph Databases2nd ed. O’Reilly, 2015
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- 18. • – • • Graph Vertex Edge Vertex IDProperties Edge ID PropertiesStart Vertex ID End Vertex ID B-tree Vertex ID B-tree (Start, End) B-tree (End, Start)
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- 20. • Edge Edge ID PropertiesStartVertex ID End Vertex ID B-tree (Start, End) B-tree (End, Start) Edge ID Properties B-tree or Hash index (Vertex ID) (Adjacent Vertex ID, Edge ID) B-tree (Edge ID)
- 21. • • • Vertex ID Properties ag_vertex VertexID Properties Person Vertex ID Properties Message Vertex ID Properties Comment Vertex ID Properties Post
- 22. • AgensGraph v0.9 (https://github.com/bitnine-oss/agens-graphor http://bitnine.net/downloads/) – Graph data model and DDL on PostgreSQL 9.6 – Cypher query processing (70% of OpenCypher spec.) – Integrated query processing (Cypher + SQL) – Client library (JDBC, ODBC, Python) – Monitoring and development using Tadpole DB-hub
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- 29. Person Country:X Person :knows*1..2 Message Given a startPerson, find Persons that are their friends and friends of friends that have made Messages in both of the given Countries, X and Y, within a given period. Only Persons that are foreign to Countries X and Y are considered, that is Persons whose Location is not Country X or Country Y.
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