This document provides an introduction to Neo4j and graph databases. It covers what a graph is, why graphs are useful for modeling real-world problems, the basic components of a graph database, and an introduction to the Cypher query language. It also describes hands-on examples using the Neo4j sandbox to model and query graph data. Finally, it provides resources for continuing to learn about Neo4j and graph databases.

1. Introduction to Neo4j - a
hands-on crash course
Lju Lazarevic
lju@neo4j.com
@ellazal
community.neo4j.com

2. In this session
We will cover:
• What is a graph and why we need them
• Spotting good graph scenarios
• Property graph database anatomy and introduction to Cypher
• Hands-on: the movie graph on sandbox
• sandbox.neo4j.com
• Continuing your graph journey

3. What is a graph?

4. A graph is...
...a set of discrete objects, each of which has some set of relationships with
the other objects
Seven Bridges of Konigsberg problem. Leonhard Euler, 1735

5. Anything can be a graph
the Internet a water molecule
H
O
H

6. Why do we need graphs?

7. Reality
seldom
comes in
discrete
tables
Customer
Beverage
Mapping
Action
CI Name
BI Name AI Type
CI BI AIProblems are
best understood
with a
representation
of reality
Reality is often
about things
being
connected to
other things
drinks in store
A graph
provides a
better
approximation
of reality
Customer
Coffee
DRINKS
Reality does
not stop at
the border
of a data
silo
Customer
Product
Order
19 Jason
32 Ann
91 Dan
11 Filter
21 Latte
31 Flat W.
01 Buy
04 Preord.
09 Drink
91 21 01
91 21 09
32 11 04

9. Follow the flow - buying trainers

10. Panama papers:
simple model, powerful
outcome

11. The Panama papers data
model...

12. Roses are red,
facebook is blue,
No mutual friends,
So who are you?

13. Friends of friends
...or co-actors of co-actors

14. What are good graph
scenarios?

15. Scenario 1: Does our problem involve understanding relationships
between entities?
Identifying good graph scenarios
● Recommendations
● Fraud detection
● Finding duplicates
● Data lineage

16. Scenario 2: Does the problem involve a lot of self-referencing to the
same type of entity?
Identifying good graph scenarios
● Organisational
hierarchies
● Access management
● Social influencers
● Friends of friends

17. Scenario 3: Does the problem explore relationships of varying or
unknown depth?
Identifying good graph scenarios
● Supply chain
visibility
● Bill of Materials
● Network
management

18. Scenario 4: Does our problem involve discovering lots of different
routes or paths?
Identifying good graph scenarios
● Logistics and routing
● Infrastructure
management
● Dependency tracing

19. So what does a (property)
graph look like?

20. Node (Vertex)
● The main data element from which graphs are constructed
Graph components
Jane car

21. Graph components
Node (Vertex)
● The main data element from which graphs are constructed
Relationship (Edge)
● A link between two nodes. Has:
○ Direction
○ Type
● A node without relationships is permitted. A relationship without nodes is not
Jane carOWNS

22. Label property graph database
Node (Vertex)
Relationship (Edge)
OWNS

23. Label property graph database
Node (Vertex)
Relationship (Edge)
:Person :CarOWNS
Label
● Define node category (optional)

24. Label property graph database
Node (Vertex)
Relationship (Edge)
:Person :CarOWNS
Label
● Define node category (optional)
● Can have more than one
:Asset

25. Node (Vertex)
Relationship (Edge)
:Person :CarOWNS
Label
● Define node category (optional)
● Can have more than one
Properties
● Enrich a node or relationship
● No need for nulls!
name: Jane make: Volvo
model: V60
since: 2018
:Asset
Label property graph database

26. How do I query the graph?

27. 27

Cypher

28. 28

Cypher

29. 29

Cypher
ツ

30. Use MATCH to retrieve nodes
//Match all nodes
MATCH (n)
RETURN n;

31. Use MATCH to retrieve nodes
//Match all nodes
MATCH (n)
RETURN n;
//Match all nodes with a Person label
MATCH (n:Person)
RETURN n;

32. Use MATCH to retrieve nodes
//Match all nodes
MATCH (n)
RETURN n;
//Match all nodes with a Person label
MATCH (n:Person)
RETURN n;
//Match all nodes with a Person label and property name is "Tom Hanks"
MATCH (n:Person {name: "Tom Hanks"})
RETURN n;

33. //Return nodes with label Person and name property is "Tom Hanks" - Inline
MATCH (p:Person {name: "Tom Hanks"}) //Only works with exact matches
RETURN p;
Use MATCH and properties to retrieve nodes

34. //Return nodes with label Person and name property is "Tom Hanks" - Inline
MATCH (p:Person {name: "Tom Hanks"}) //Only works with exact matches
RETURN p;
//Return nodes with label Person and name property equals "Tom Hanks"
MATCH (p:Person)
WHERE p.name = "Tom Hanks"
RETURN p;
Use MATCH and properties to retrieve nodes

35. //Return nodes with label Person and name property is "Tom Hanks" - Inline
MATCH (p:Person {name: "Tom Hanks"}) //Only works with exact matches
RETURN p;
//Return nodes with label Person and name property equals "Tom Hanks"
MATCH (p:Person)
WHERE p.name = "Tom Hanks"
RETURN p;
//Return nodes with label Movie, released property is between 1991 and
1999
MATCH (m:Movie)
WHERE m.released > 1990 AND m.released < 2000
RETURN m;
Use MATCH and properties to retrieve nodes

36. Extending the MATCH

37. //Find all the movies Tom Hanks acted in
MATCH (:Person {name:"Tom Hanks"})-[:ACTED_IN]->(m:Movie)
RETURN m.title;
Extending the MATCH

38. //Find all the movies Tom Hanks acted in
MATCH (:Person {name:"Tom Hanks"})-[:ACTED_IN]->(m:Movie)
RETURN m.title;
//Find all the movies Tom Hanks directed and order by latest movie
MATCH (:Person {name:"Tom Hanks"})-[:DIRECTED]->(m:Movie)
RETURN m.title, m.released ORDER BY m.released DESC;
Extending the MATCH

39. //Find all the movies Tom Hanks acted in
MATCH (:Person {name:"Tom Hanks"})-[:ACTED_IN]->(m:Movie)
RETURN m.title;
//Find all the movies Tom Hanks directed and order by latest movie
MATCH (:Person {name:"Tom Hanks"})-[:DIRECTED]->(m:Movie)
RETURN m.title, m.released ORDER BY m.released DESC;
//Find all of the co-actors Tom Hanks have worked with
MATCH (:Person {name:"Tom
Hanks"})-->(:Movie)<-[:ACTED_IN]-(coActor:Person)
Extending the MATCH

40. //Create a person node called "Tom Hanks"
CREATE (p:Person {name:"Tom Hanks"});
CREATE

41. //Create a person node called "Tom Hanks"
CREATE (p:Person {name:"Tom Hanks"});
//Create an ACTED_IN relationship between "Tom Hanks" and "Apollo 13"
MATCH (p:Person {name:"Tom Hanks"}), (m:Movie {title:"Apollo 13"})
CREATE (p)-[:ACTED_IN]->(m);
CREATE

42. //Create a person node called "Tom Hanks"
CREATE (p:Person {name:"Tom Hanks"});
//Create an ACTED_IN relationship between "Tom Hanks" and "Apollo 13"
MATCH (p:Person {name:"Tom Hanks"}), (m:Movie {title:"Apollo 13"})
CREATE (p)-[:ACTED_IN]->(m);
//Create the pattern of "Tom Hanks" ACTED_IN "Apollo 13"
//This will create the entire pattern, nodes and all!
CREATE (:Person {name:"Tom Hanks")-[:ACTED_IN]->(:Movie {title:"Apollo
13});
CREATE

43. Time to have a go!
We are going to:
• Go to sandbox.neo4j.com
• Sign in
• Select "Blank sandbox" and click Launch Project
We’ll all have a go together :)

44. So how do I continue my
graph journey?

45. Free book:
neo4j.com/graph-databases-book
Free online training and certification:
neo4j.com/graphacademy/online-training
How to, best practices and customer
stories:
youtube.com/neo4j

46. But you can still have a go at these fun challenges at
your own pace!
• Modelling a barbecue
• Exploring a museum collection
• Solving a murder mystery
• Virtually visiting Central Park
Start here: r.neo4j.com/son-week1
Summer of Nodes is over...

47. Ljubica Lazarevic
Developer Relations
Advocate
@ElLazal
lju@neo4j.com
Join the conversation at community.neo4j.com