graph database
DESCRIPTION
Introduction to the applications of graph databasesTRANSCRIPT
NOSQL GRAPH DBs
APP NEO4J
AGENDA
Graph Databases
Graph Databases
Leonhard Euler (1707 –1783) Swiss mathematician
Graph Databases: HISTORY
Graph Databases: HISTORY
What is Graph?
A B
C D
Ver%ce (Node)
Edge (Rela%onship)
Graph Databases: GRAPH
Graph Databases: WHAT IS IT?
Graph Databases: WHAT IS IT?
Joins VS Traversals
Good for semi-structured connected
data
1 Index free-
adjacency
The underlying
storage
The processing
engine
2
3
4
Graph Databases: CHARACTERISTICS
APPs
ApplicaFon: social graphs
Application: PAGE RANK
APP: Collaborative filtering
Neo4J: CHARACTERISTICS
true ACID transac%ons; scales to billions of nodes and rela%onships; high speed querying through traversals; declara%ve graph query language;
Neo4J: who use it
Neo4J: WHO USE
Neo4J: network architecture
Neo4J: who use it
Neo4J: NETWORK ARCHITECTURE
Neo4J: architecture Neo4J: ARCHITECTURE
Neo4J: architecture Neo4J: Internal storage
Node
Rela%onship
Neo4J: architecture Neo4J: Internal storage
APP: Collaborative filtering Neo4J: CF
APP: Collaborative filtering Neo4J: CF
Neo4J: CYPHER
MATCH (p1:Person)-‐[x:RATED]-‐>(m:PRODUCT)<-‐[y:RATED]-‐
(p2:Person) WITH
SUM(x.ra%ng * y.ra%ng) AS xyDotProduct, SQRT(REDUCE(xDot = 0, a IN COLLECT(x.ra%ng) | xDot + a^2)) AS xLength, SQRT(REDUCE(yDot = 0, b IN COLLECT(y.ra%ng) | yDot + b^2)) AS yLength, p1, p2 CREATE UNIQUE
(p1)-‐[s:SIMILARITY]-‐(p2) SET
s.similarity = xyDotProduct / (xLength * yLength)
