SlideShare a Scribd company logo
Intro to Graphs
All the meetups
What’s a graph database?
Simply put, a graph consists of nodes connected by relationships.
Graph databases store data as graph structures (nodes and relationships)
Neo4j Fundamentals
• Nodes
• Relationships
• Properties
• Labels
CAR
Property Graph Model Components
Nodes
• Represent the objects in the graph
• Can be labeled
PERSON PERSON
CAR
DRIVES
Property Graph Model Components
Nodes
• Represent the objects in the graph
• Can be labeled
Relationships
• Relate nodes by type and direction
LOVES
LOVES
LIVES WITH
OW
NS
PERSON PERSON
CAR
DRIVES
name: “Dan”
born: May 29, 1970
twitter: “@dan”
name: “Ann”
born: Dec 5, 1975
since:
Jan 10, 2011
brand: “Volvo”
model: “V70”
Property Graph Model Components
Nodes
• Represent the objects in the graph
• Can be labeled
Relationships
• Relate nodes by type and direction
Properties
• Name-value pairs that can go on
nodes and relationships.
LOVES
LOVES
LIVES WITH
OW
NS
PERSON PERSON
Graphs are all around us
Can you identify nodes and relationships related to this meetup?
Summary of the graph building blocks
• Nodes - Entities and complex value types
• Relationships - Connect entities and structure domain
• Properties - Entity attributes, relationship qualities, metadata
• Labels - Group nodes by role
Cypher: Graph Query Language
MATCH (:Person { name:"Dan"} ) -[:LOVES]-> (:Person { name:"Ann"} )
LOVES
Dan Ann
LABEL PROPERTY
NODE NODE
LABEL PROPERTY
Let's get started
With ASCII ART ¯_(ツ)_/¯
Nodes
() or (n)
• Surrounded with parentheses
• Use an alias n to refer to our node later in the query
Nodes
() or (n)
• Surrounded with parentheses
• Use an alias n to refer to our node later in the query
(n:Label)
• Specify a Label, starting with a colon :
• Used to group nodes by roles or types (similar to tags)
Nodes
() or (n)
• Surrounded with parentheses
• Use an alias n to refer to our node later in the query
(n:Label)
• Specify a Label, starting with a colon :
• Used to group nodes by roles or types (similar to tags)
(n:Label {prop: 'value'})
• Nodes can have properties
--> or -[r:TYPE]->
• Wrapped with hyphens & square brackets
• A relationship type starts with a colon :
Relationships
--> or -[r:TYPE]->
• Wrapped with hyphens & square brackets
• A relationship type starts with a colon :
< > Specify the direction of the relationship
-[:KNOWS {since: 2010}]->
• Relationships can have properties too!
Relationships
• Used to query data
(n:Label {prop:'value'})-[:TYPE]->(m:Label)
Patterns
• Can you translate this pattern?
(p1:Person {name:'Alice'})-[:KNOWS]->(p2:Person {name:'Bob')
Patterns
• Find Alice who knows Bob
• In other words:
• find Person named 'Alice'
• who KNOWS
• a Person named 'Bob'
(p1:Person {name:'Alice'})-[:KNOWS]->(p2:Person {name:'Bob'})
Patterns
Demo
Navigate to neo4j.com/download
Installing Neo4j
Once you download,
For setup you will be asked to give a default location.
Click start! You are good to go.
Goto Browser type http://localhost:7474 Enter default password: neo4j
Instructions
Type :play movies into the query bar:
The movies graph
Type :play movies into the query bar:
The movies graph
Sample Queries to try out
// Find the Matrix
MATCH (movie:Movie {title:"The Matrix"})
RETURN movie
// Find the people who acted in any movie and return their name and
// the role they played in the movie
MATCH (actor:Person)-[rel:ACTED_IN]->(movie:Movie)
RETURN rel.roles, actor.name
Building an application
Language Drivers
Java
<dependency>
<groupId>org.neo4j.driver</groupId>
<artifactId>neo4j-java-driver</artifactId>
</dependency>
Python
pip install neo4j-driver
.NET
PM> Install-Package Neo4j.Driver
JavaScript
npm install neo4j-driver
Architecture and Data Flow
Application
Cypher Bolt Driver
Cypher Bolt Server
MATCH (a:Person)
WHERE a.name = 'Alice'
RETURN a.surname, a.age
{surname: 'Smith',
age: 33}
Parameterised
Cypher
Result
Stream
metadata
Driver -> Neo4j example
from neo4j.v1 import GraphDatabase, basic_auth
driver = GraphDatabase.driver("bolt://localhost", auth=basic_auth("neo4j", "neo4j"))
session = driver.session()
session.run("CREATE (a:Person {name:'Arthur', title:'King'})")
result = session.run("""MATCH (a:Person)
WHERE a.name = 'Arthur'
RETURN a.name AS name, a.title AS title""")
for record in result:
print("%s %s" % (record["title"], record["name"]))
session.close()
Who’s using Neo4j?
How Customers Use Neo4j
Network &
Data Center
Master Data
Management
Social Recommendations
Identity &
Access
Search &
Discovery
GEO
What next?
If you like meetups...
meetup.com/graphdb-london
If you like reading...
graphdatabases.com
If you like videos...
youtube.com/neo4j
If you like getting your hands dirty...
neo4j.com/online_training/graphdatabases
If you get stuck....
http://stackoverflow.com/tags/neo4j
http://neo4j.com/slack
In summary
• Flexible, iterative way of modeling data
• 4 building blocks - nodes, relationships, properties, labels
• Cypher Query Language - executable ASCII art
• Language drivers - Java, Javascript, .NET, Python

More Related Content

What's hot

The Knowledge Graph Explosion
The Knowledge Graph ExplosionThe Knowledge Graph Explosion
The Knowledge Graph Explosion
Neo4j
 
Building a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and OntologiesBuilding a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and Ontologies
Neo4j
 
Neo4j GraphTalk Helsinki - Introduction and Graph Use Cases
Neo4j GraphTalk Helsinki - Introduction and Graph Use CasesNeo4j GraphTalk Helsinki - Introduction and Graph Use Cases
Neo4j GraphTalk Helsinki - Introduction and Graph Use Cases
Neo4j
 
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptxThe art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
Neo4j
 
Using Knowledge Graphs to Predict Customer Needs and Improve Quality
Using Knowledge Graphs to Predict Customer Needs and Improve QualityUsing Knowledge Graphs to Predict Customer Needs and Improve Quality
Using Knowledge Graphs to Predict Customer Needs and Improve Quality
Neo4j
 
Knowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based SearchKnowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based Search
Neo4j
 
Neo4J 사용
Neo4J 사용Neo4J 사용
Neo4J 사용
홍수 허
 
Elsevier: Empowering Knowledge Discovery in Research with Graphs
Elsevier: Empowering Knowledge Discovery in Research with GraphsElsevier: Empowering Knowledge Discovery in Research with Graphs
Elsevier: Empowering Knowledge Discovery in Research with Graphs
Neo4j
 
Graph-Based Customer Journey Analytics with Neo4j
Graph-Based Customer Journey Analytics with Neo4jGraph-Based Customer Journey Analytics with Neo4j
Graph-Based Customer Journey Analytics with Neo4j
Neo4j
 
Neo4j 4 Overview
Neo4j 4 OverviewNeo4j 4 Overview
Neo4j 4 Overview
Neo4j
 
Building a modern data stack to maintain an efficient and safe electrical grid
Building a modern data stack to maintain an efficient and safe electrical gridBuilding a modern data stack to maintain an efficient and safe electrical grid
Building a modern data stack to maintain an efficient and safe electrical grid
Neo4j
 
Neo4j GraphDay Seattle- Sept19- neo4j basic training
Neo4j GraphDay Seattle- Sept19- neo4j basic trainingNeo4j GraphDay Seattle- Sept19- neo4j basic training
Neo4j GraphDay Seattle- Sept19- neo4j basic training
Neo4j
 
Slides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property GraphsSlides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property Graphs
DATAVERSITY
 
Graph database Use Cases
Graph database Use CasesGraph database Use Cases
Graph database Use Cases
Max De Marzi
 
Migrating Netflix from Datacenter Oracle to Global Cassandra
Migrating Netflix from Datacenter Oracle to Global CassandraMigrating Netflix from Datacenter Oracle to Global Cassandra
Migrating Netflix from Datacenter Oracle to Global Cassandra
Adrian Cockcroft
 
Building the Rail Network Digital Twin at CSX
Building the Rail Network Digital Twin at CSXBuilding the Rail Network Digital Twin at CSX
Building the Rail Network Digital Twin at CSX
Neo4j
 
Training Week: Introduction to Neo4j
Training Week: Introduction to Neo4jTraining Week: Introduction to Neo4j
Training Week: Introduction to Neo4j
Neo4j
 
The openCypher Project - An Open Graph Query Language
The openCypher Project - An Open Graph Query LanguageThe openCypher Project - An Open Graph Query Language
The openCypher Project - An Open Graph Query Language
Neo4j
 
Intro to Neo4j - Nicole White
Intro to Neo4j - Nicole WhiteIntro to Neo4j - Nicole White
Intro to Neo4j - Nicole White
Neo4j
 
Intro to Neo4j and Graph Databases
Intro to Neo4j and Graph DatabasesIntro to Neo4j and Graph Databases
Intro to Neo4j and Graph Databases
Neo4j
 

What's hot (20)

The Knowledge Graph Explosion
The Knowledge Graph ExplosionThe Knowledge Graph Explosion
The Knowledge Graph Explosion
 
Building a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and OntologiesBuilding a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and Ontologies
 
Neo4j GraphTalk Helsinki - Introduction and Graph Use Cases
Neo4j GraphTalk Helsinki - Introduction and Graph Use CasesNeo4j GraphTalk Helsinki - Introduction and Graph Use Cases
Neo4j GraphTalk Helsinki - Introduction and Graph Use Cases
 
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptxThe art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
The art of the possible with graph technology_Neo4j GraphSummit Dublin 2023.pptx
 
Using Knowledge Graphs to Predict Customer Needs and Improve Quality
Using Knowledge Graphs to Predict Customer Needs and Improve QualityUsing Knowledge Graphs to Predict Customer Needs and Improve Quality
Using Knowledge Graphs to Predict Customer Needs and Improve Quality
 
Knowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based SearchKnowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based Search
 
Neo4J 사용
Neo4J 사용Neo4J 사용
Neo4J 사용
 
Elsevier: Empowering Knowledge Discovery in Research with Graphs
Elsevier: Empowering Knowledge Discovery in Research with GraphsElsevier: Empowering Knowledge Discovery in Research with Graphs
Elsevier: Empowering Knowledge Discovery in Research with Graphs
 
Graph-Based Customer Journey Analytics with Neo4j
Graph-Based Customer Journey Analytics with Neo4jGraph-Based Customer Journey Analytics with Neo4j
Graph-Based Customer Journey Analytics with Neo4j
 
Neo4j 4 Overview
Neo4j 4 OverviewNeo4j 4 Overview
Neo4j 4 Overview
 
Building a modern data stack to maintain an efficient and safe electrical grid
Building a modern data stack to maintain an efficient and safe electrical gridBuilding a modern data stack to maintain an efficient and safe electrical grid
Building a modern data stack to maintain an efficient and safe electrical grid
 
Neo4j GraphDay Seattle- Sept19- neo4j basic training
Neo4j GraphDay Seattle- Sept19- neo4j basic trainingNeo4j GraphDay Seattle- Sept19- neo4j basic training
Neo4j GraphDay Seattle- Sept19- neo4j basic training
 
Slides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property GraphsSlides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property Graphs
 
Graph database Use Cases
Graph database Use CasesGraph database Use Cases
Graph database Use Cases
 
Migrating Netflix from Datacenter Oracle to Global Cassandra
Migrating Netflix from Datacenter Oracle to Global CassandraMigrating Netflix from Datacenter Oracle to Global Cassandra
Migrating Netflix from Datacenter Oracle to Global Cassandra
 
Building the Rail Network Digital Twin at CSX
Building the Rail Network Digital Twin at CSXBuilding the Rail Network Digital Twin at CSX
Building the Rail Network Digital Twin at CSX
 
Training Week: Introduction to Neo4j
Training Week: Introduction to Neo4jTraining Week: Introduction to Neo4j
Training Week: Introduction to Neo4j
 
The openCypher Project - An Open Graph Query Language
The openCypher Project - An Open Graph Query LanguageThe openCypher Project - An Open Graph Query Language
The openCypher Project - An Open Graph Query Language
 
Intro to Neo4j - Nicole White
Intro to Neo4j - Nicole WhiteIntro to Neo4j - Nicole White
Intro to Neo4j - Nicole White
 
Intro to Neo4j and Graph Databases
Intro to Neo4j and Graph DatabasesIntro to Neo4j and Graph Databases
Intro to Neo4j and Graph Databases
 

Similar to Introduction to Graphs with Neo4j

Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH)
Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH) Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH)
Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH)
David Fombella Pombal
 
Neo4j (Part 1)
Neo4j (Part 1)Neo4j (Part 1)
Neo4j (Part 1)
Bibhuti Regmi
 
Neo4J Open Source Graph Database
Neo4J Open Source Graph DatabaseNeo4J Open Source Graph Database
Neo4J Open Source Graph Database
Mark Maslyn
 
Hands on Training – Graph Database with Neo4j
Hands on Training – Graph Database with Neo4jHands on Training – Graph Database with Neo4j
Hands on Training – Graph Database with Neo4j
Serendio Inc.
 
Demo Neo4j - Big Data Paris
Demo Neo4j - Big Data ParisDemo Neo4j - Big Data Paris
Demo Neo4j - Big Data Paris
Neo4j
 
Morpheus - Cypher for Apache Spark
Morpheus - Cypher for Apache SparkMorpheus - Cypher for Apache Spark
Morpheus - Cypher for Apache Spark
Knoldus Inc.
 
Elixir + Neo4j
Elixir + Neo4jElixir + Neo4j
Elixir + Neo4j
Regina Imhoff
 
Neo4j graphdatabaseforrecommendations-130531021030-phpapp02-converted
Neo4j graphdatabaseforrecommendations-130531021030-phpapp02-convertedNeo4j graphdatabaseforrecommendations-130531021030-phpapp02-converted
Neo4j graphdatabaseforrecommendations-130531021030-phpapp02-converted
snehapandey01
 
Neo4j - graph database for recommendations
Neo4j - graph database for recommendationsNeo4j - graph database for recommendations
Neo4j - graph database for recommendations
proksik
 
The 2nd graph database in sv meetup
The 2nd graph database in sv meetupThe 2nd graph database in sv meetup
The 2nd graph database in sv meetup
Joshua Bae
 
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Databricks
 
Neo4j Davide Francesconi
Neo4j Davide FrancesconiNeo4j Davide Francesconi
Neo4j Davide Francesconi
Davide Francesconi
 
Introduction to graph databases in term of neo4j
Introduction to graph databases in term of neo4jIntroduction to graph databases in term of neo4j
Introduction to graph databases in term of neo4j
Abdullah Hamidi
 
Windy City DB - Recommendation Engine with Neo4j
Windy City DB - Recommendation Engine with Neo4jWindy City DB - Recommendation Engine with Neo4j
Windy City DB - Recommendation Engine with Neo4j
Max De Marzi
 
Introduction to neo4j - a hands-on crash course
Introduction to neo4j - a hands-on crash courseIntroduction to neo4j - a hands-on crash course
Introduction to neo4j - a hands-on crash course
Neo4j
 
Data modeling with neo4j tutorial
Data modeling with neo4j tutorialData modeling with neo4j tutorial
Data modeling with neo4j tutorial
Max De Marzi
 
The Football Graph - Neo4j and the Premier League
The Football Graph - Neo4j and the Premier LeagueThe Football Graph - Neo4j and the Premier League
The Football Graph - Neo4j and the Premier League
Mark Needham
 
03 introduction to graph databases
03   introduction to graph databases03   introduction to graph databases
03 introduction to graph databases
Neo4j
 
Making Topicmaps SPARQL
Making Topicmaps SPARQLMaking Topicmaps SPARQL
Making Topicmaps SPARQL
NetworkedPlanet
 
Introduction to graph databases, Neo4j and Spring Data - English 2015 Edition
Introduction to graph databases, Neo4j and Spring Data - English 2015 EditionIntroduction to graph databases, Neo4j and Spring Data - English 2015 Edition
Introduction to graph databases, Neo4j and Spring Data - English 2015 Edition
Aleksander Stensby
 

Similar to Introduction to Graphs with Neo4j (20)

Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH)
Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH) Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH)
Neo4j Introduction (Basics, Cypher, RDBMS to GRAPH)
 
Neo4j (Part 1)
Neo4j (Part 1)Neo4j (Part 1)
Neo4j (Part 1)
 
Neo4J Open Source Graph Database
Neo4J Open Source Graph DatabaseNeo4J Open Source Graph Database
Neo4J Open Source Graph Database
 
Hands on Training – Graph Database with Neo4j
Hands on Training – Graph Database with Neo4jHands on Training – Graph Database with Neo4j
Hands on Training – Graph Database with Neo4j
 
Demo Neo4j - Big Data Paris
Demo Neo4j - Big Data ParisDemo Neo4j - Big Data Paris
Demo Neo4j - Big Data Paris
 
Morpheus - Cypher for Apache Spark
Morpheus - Cypher for Apache SparkMorpheus - Cypher for Apache Spark
Morpheus - Cypher for Apache Spark
 
Elixir + Neo4j
Elixir + Neo4jElixir + Neo4j
Elixir + Neo4j
 
Neo4j graphdatabaseforrecommendations-130531021030-phpapp02-converted
Neo4j graphdatabaseforrecommendations-130531021030-phpapp02-convertedNeo4j graphdatabaseforrecommendations-130531021030-phpapp02-converted
Neo4j graphdatabaseforrecommendations-130531021030-phpapp02-converted
 
Neo4j - graph database for recommendations
Neo4j - graph database for recommendationsNeo4j - graph database for recommendations
Neo4j - graph database for recommendations
 
The 2nd graph database in sv meetup
The 2nd graph database in sv meetupThe 2nd graph database in sv meetup
The 2nd graph database in sv meetup
 
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
 
Neo4j Davide Francesconi
Neo4j Davide FrancesconiNeo4j Davide Francesconi
Neo4j Davide Francesconi
 
Introduction to graph databases in term of neo4j
Introduction to graph databases in term of neo4jIntroduction to graph databases in term of neo4j
Introduction to graph databases in term of neo4j
 
Windy City DB - Recommendation Engine with Neo4j
Windy City DB - Recommendation Engine with Neo4jWindy City DB - Recommendation Engine with Neo4j
Windy City DB - Recommendation Engine with Neo4j
 
Introduction to neo4j - a hands-on crash course
Introduction to neo4j - a hands-on crash courseIntroduction to neo4j - a hands-on crash course
Introduction to neo4j - a hands-on crash course
 
Data modeling with neo4j tutorial
Data modeling with neo4j tutorialData modeling with neo4j tutorial
Data modeling with neo4j tutorial
 
The Football Graph - Neo4j and the Premier League
The Football Graph - Neo4j and the Premier LeagueThe Football Graph - Neo4j and the Premier League
The Football Graph - Neo4j and the Premier League
 
03 introduction to graph databases
03   introduction to graph databases03   introduction to graph databases
03 introduction to graph databases
 
Making Topicmaps SPARQL
Making Topicmaps SPARQLMaking Topicmaps SPARQL
Making Topicmaps SPARQL
 
Introduction to graph databases, Neo4j and Spring Data - English 2015 Edition
Introduction to graph databases, Neo4j and Spring Data - English 2015 EditionIntroduction to graph databases, Neo4j and Spring Data - English 2015 Edition
Introduction to graph databases, Neo4j and Spring Data - English 2015 Edition
 

More from Neo4j

Atelier - Architecture d’applications de Graphes - GraphSummit Paris
Atelier - Architecture d’applications de Graphes - GraphSummit ParisAtelier - Architecture d’applications de Graphes - GraphSummit Paris
Atelier - Architecture d’applications de Graphes - GraphSummit Paris
Neo4j
 
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissancesAtelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Neo4j
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j
 
FLOA - Détection de Fraude - GraphSummit Paris
FLOA -  Détection de Fraude - GraphSummit ParisFLOA -  Détection de Fraude - GraphSummit Paris
FLOA - Détection de Fraude - GraphSummit Paris
Neo4j
 
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...
Neo4j
 
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...
ADEO -  Knowledge Graph pour le e-commerce, entre challenges et opportunités ...ADEO -  Knowledge Graph pour le e-commerce, entre challenges et opportunités ...
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...
Neo4j
 
GraphSummit Paris - The art of the possible with Graph Technology
GraphSummit Paris - The art of the possible with Graph TechnologyGraphSummit Paris - The art of the possible with Graph Technology
GraphSummit Paris - The art of the possible with Graph Technology
Neo4j
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Neo4j
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Neo4j
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Neo4j
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neo4j
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Neo4j
 
GraphAware - Transforming policing with graph-based intelligence analysis
GraphAware - Transforming policing with graph-based intelligence analysisGraphAware - Transforming policing with graph-based intelligence analysis
GraphAware - Transforming policing with graph-based intelligence analysis
Neo4j
 
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product UpdatesGraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
Neo4j
 
KLARNA - Language Models and Knowledge Graphs: A Systems Approach
KLARNA -  Language Models and Knowledge Graphs: A Systems ApproachKLARNA -  Language Models and Knowledge Graphs: A Systems Approach
KLARNA - Language Models and Knowledge Graphs: A Systems Approach
Neo4j
 
INGKA DIGITAL: Linked Metadata by Design
INGKA DIGITAL: Linked Metadata by DesignINGKA DIGITAL: Linked Metadata by Design
INGKA DIGITAL: Linked Metadata by Design
Neo4j
 
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4jYour enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Neo4j
 
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxBT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
Neo4j
 
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit Milan
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit MilanWorkshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit Milan
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit Milan
Neo4j
 

More from Neo4j (20)

Atelier - Architecture d’applications de Graphes - GraphSummit Paris
Atelier - Architecture d’applications de Graphes - GraphSummit ParisAtelier - Architecture d’applications de Graphes - GraphSummit Paris
Atelier - Architecture d’applications de Graphes - GraphSummit Paris
 
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissancesAtelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
 
FLOA - Détection de Fraude - GraphSummit Paris
FLOA -  Détection de Fraude - GraphSummit ParisFLOA -  Détection de Fraude - GraphSummit Paris
FLOA - Détection de Fraude - GraphSummit Paris
 
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...
 
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...
ADEO -  Knowledge Graph pour le e-commerce, entre challenges et opportunités ...ADEO -  Knowledge Graph pour le e-commerce, entre challenges et opportunités ...
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...
 
GraphSummit Paris - The art of the possible with Graph Technology
GraphSummit Paris - The art of the possible with Graph TechnologyGraphSummit Paris - The art of the possible with Graph Technology
GraphSummit Paris - The art of the possible with Graph Technology
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
 
GraphAware - Transforming policing with graph-based intelligence analysis
GraphAware - Transforming policing with graph-based intelligence analysisGraphAware - Transforming policing with graph-based intelligence analysis
GraphAware - Transforming policing with graph-based intelligence analysis
 
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product UpdatesGraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
 
KLARNA - Language Models and Knowledge Graphs: A Systems Approach
KLARNA -  Language Models and Knowledge Graphs: A Systems ApproachKLARNA -  Language Models and Knowledge Graphs: A Systems Approach
KLARNA - Language Models and Knowledge Graphs: A Systems Approach
 
INGKA DIGITAL: Linked Metadata by Design
INGKA DIGITAL: Linked Metadata by DesignINGKA DIGITAL: Linked Metadata by Design
INGKA DIGITAL: Linked Metadata by Design
 
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4jYour enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4j
 
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxBT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
 
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit Milan
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit MilanWorkshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit Milan
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit Milan
 

Recently uploaded

Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Malak Abu Hammad
 
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
SOFTTECHHUB
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
Ana-Maria Mihalceanu
 
“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
Claudio Di Ciccio
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Speck&Tech
 
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Zilliz
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
DianaGray10
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
James Anderson
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
Adtran
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
SOFTTECHHUB
 
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIEnchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Vladimir Iglovikov, Ph.D.
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems S.M.S.A.
 
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
DianaGray10
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Paige Cruz
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
Matthew Sinclair
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
mikeeftimakis1
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Zilliz
 

Recently uploaded (20)

Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
 
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
 
“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
 
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
 
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIEnchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
 
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
 

Introduction to Graphs with Neo4j

  • 3.
  • 4.
  • 5.
  • 6. What’s a graph database? Simply put, a graph consists of nodes connected by relationships. Graph databases store data as graph structures (nodes and relationships)
  • 7. Neo4j Fundamentals • Nodes • Relationships • Properties • Labels
  • 8. CAR Property Graph Model Components Nodes • Represent the objects in the graph • Can be labeled PERSON PERSON
  • 9. CAR DRIVES Property Graph Model Components Nodes • Represent the objects in the graph • Can be labeled Relationships • Relate nodes by type and direction LOVES LOVES LIVES WITH OW NS PERSON PERSON
  • 10. CAR DRIVES name: “Dan” born: May 29, 1970 twitter: “@dan” name: “Ann” born: Dec 5, 1975 since: Jan 10, 2011 brand: “Volvo” model: “V70” Property Graph Model Components Nodes • Represent the objects in the graph • Can be labeled Relationships • Relate nodes by type and direction Properties • Name-value pairs that can go on nodes and relationships. LOVES LOVES LIVES WITH OW NS PERSON PERSON
  • 11. Graphs are all around us Can you identify nodes and relationships related to this meetup?
  • 12. Summary of the graph building blocks • Nodes - Entities and complex value types • Relationships - Connect entities and structure domain • Properties - Entity attributes, relationship qualities, metadata • Labels - Group nodes by role
  • 13. Cypher: Graph Query Language MATCH (:Person { name:"Dan"} ) -[:LOVES]-> (:Person { name:"Ann"} ) LOVES Dan Ann LABEL PROPERTY NODE NODE LABEL PROPERTY
  • 14. Let's get started With ASCII ART ¯_(ツ)_/¯
  • 15. Nodes () or (n) • Surrounded with parentheses • Use an alias n to refer to our node later in the query
  • 16. Nodes () or (n) • Surrounded with parentheses • Use an alias n to refer to our node later in the query (n:Label) • Specify a Label, starting with a colon : • Used to group nodes by roles or types (similar to tags)
  • 17. Nodes () or (n) • Surrounded with parentheses • Use an alias n to refer to our node later in the query (n:Label) • Specify a Label, starting with a colon : • Used to group nodes by roles or types (similar to tags) (n:Label {prop: 'value'}) • Nodes can have properties
  • 18. --> or -[r:TYPE]-> • Wrapped with hyphens & square brackets • A relationship type starts with a colon : Relationships
  • 19. --> or -[r:TYPE]-> • Wrapped with hyphens & square brackets • A relationship type starts with a colon : < > Specify the direction of the relationship -[:KNOWS {since: 2010}]-> • Relationships can have properties too! Relationships
  • 20. • Used to query data (n:Label {prop:'value'})-[:TYPE]->(m:Label) Patterns
  • 21. • Can you translate this pattern? (p1:Person {name:'Alice'})-[:KNOWS]->(p2:Person {name:'Bob') Patterns
  • 22. • Find Alice who knows Bob • In other words: • find Person named 'Alice' • who KNOWS • a Person named 'Bob' (p1:Person {name:'Alice'})-[:KNOWS]->(p2:Person {name:'Bob'}) Patterns
  • 23. Demo
  • 25. Once you download, For setup you will be asked to give a default location. Click start! You are good to go. Goto Browser type http://localhost:7474 Enter default password: neo4j Instructions
  • 26. Type :play movies into the query bar: The movies graph
  • 27. Type :play movies into the query bar: The movies graph
  • 28. Sample Queries to try out // Find the Matrix MATCH (movie:Movie {title:"The Matrix"}) RETURN movie // Find the people who acted in any movie and return their name and // the role they played in the movie MATCH (actor:Person)-[rel:ACTED_IN]->(movie:Movie) RETURN rel.roles, actor.name
  • 31. Architecture and Data Flow Application Cypher Bolt Driver Cypher Bolt Server MATCH (a:Person) WHERE a.name = 'Alice' RETURN a.surname, a.age {surname: 'Smith', age: 33} Parameterised Cypher Result Stream metadata
  • 32. Driver -> Neo4j example from neo4j.v1 import GraphDatabase, basic_auth driver = GraphDatabase.driver("bolt://localhost", auth=basic_auth("neo4j", "neo4j")) session = driver.session() session.run("CREATE (a:Person {name:'Arthur', title:'King'})") result = session.run("""MATCH (a:Person) WHERE a.name = 'Arthur' RETURN a.name AS name, a.title AS title""") for record in result: print("%s %s" % (record["title"], record["name"])) session.close()
  • 34. How Customers Use Neo4j Network & Data Center Master Data Management Social Recommendations Identity & Access Search & Discovery GEO
  • 36. If you like meetups... meetup.com/graphdb-london
  • 37. If you like reading... graphdatabases.com
  • 38. If you like videos... youtube.com/neo4j
  • 39. If you like getting your hands dirty... neo4j.com/online_training/graphdatabases
  • 40. If you get stuck.... http://stackoverflow.com/tags/neo4j http://neo4j.com/slack
  • 41. In summary • Flexible, iterative way of modeling data • 4 building blocks - nodes, relationships, properties, labels • Cypher Query Language - executable ASCII art • Language drivers - Java, Javascript, .NET, Python