The document introduces Cypher, the declarative query language for Neo4j. It explains that Cypher uses ASCII art syntax to represent graph patterns and identify patterns in graph data. Nodes represent entities and can have labels and properties, relationships connect nodes and have types and properties. Examples show how to write Cypher queries to create, read, and match patterns in a movie database graph.

1. Introduction to Cypher
Adam Cowley
Developer Advocate - @adamcowley

3. Toy
Story

4. Toy
Story
Nodes represent
things

5. Toy
Story
Movie
Nodes represent
things

6. Toy
Story
Movie
Nodes can be identified by
one or more labels
Nodes represent
things

7. Toy
Story
Movie
Animated
Nodes can be identified by
one or more labels
Nodes represent
things

8. Toy
Story
Movie
Animated
Nodes can be identified by
one or more labels
title: Toy Story
released: 1995
Nodes represent
things

9. Toy
Story
Movie
Animated
Nodes can be identified by
one or more labels
title: Toy Story
released: 1995
Nodes represent
things
Nodes can hold
properties as key/value
pairs

10. Toy
Story
Movie

11. Tom
Hanks
Actor
Toy
Story
Movie

12. Toy
Story
Movie
Tom
Hanks
Actor

13. Toy
Story
Movie
Tom
Hanks
Actor
Relationships connect two nodes

14. Toy
Story
Movie
Tom
Hanks
Actor
Relationships connect two nodes
ACTED_IN

15. Toy
Story
Movie
Tom
Hanks
Actor
Relationships connect two nodes
ACTED_IN
Relationships
have a type

16. Toy
Story
Movie
Tom
Hanks
Actor
Relationships connect two nodes
ACTED_IN
Relationships
have a type
Relationships
have a direction

17. Toy
Story
Movie
Tom
Hanks
Actor
Relationships connect two nodes
ACTED_IN
roles: Woody
Relationships
have a type
Relationships
have a direction

18. Toy
Story
Movie
Tom
Hanks
Actor
Relationships connect two nodes
ACTED_IN
roles: Woody
Relationships
have a type
Relationships can also
hold properties as
key/value pairs
Relationships
have a direction

19. Cypher

20. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.

21. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.

22. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person

23. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

24. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

25. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

26. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

27. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

28. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

29. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

30. Cypher is a declarative language that allows you
to identify patterns in your data using an ASCII-
art style syntax consisting of brackets, dashes
and arrows.
Movie
ACTED_IN
Person
(p:Person)-[r:ACTED_IN]->(m:Movie)

31. Writing to Neo4j
// Create a pattern
CREATE (:Person {name: "Tom Hanks"})
-[:ACTED_IN {roles: "Woody"}]->
(:Movie {title: "Toy Story"})

32. Writing to Neo4j
// Find or create using MERGE
MERGE (p:Person {name: "Tom Hanks"})

33. Writing to Neo4j
// Find or create using MERGE
MERGE (p:Person {name: "Tom Hanks"})
MERGE (m:Movie {title: "Toy Story"})

34. Writing to Neo4j
// Find or create using MERGE
MERGE (p:Person {name: "Tom Hanks"})
MERGE (m:Movie {title: "Toy Story"})
MERGE (p)-[r:ACTED_IN]->(m)

35. Writing to Neo4j
// Find or create using MERGE
MERGE (p:Person {name: "Tom Hanks"})
MERGE (m:Movie {title: "Toy Story"})
MERGE (p)-[r:ACTED_IN]->(m)
SET r.roles = "Woody"

36. Reading from Neo4j
// Find a pattern in the database
MATCH (p:Person)-[r:ACTED_IN]->(m:Movie)

37. Reading from Neo4j
// Find a pattern in the database
MATCH (p:Person)-[r:ACTED_IN]->(m:Movie)
// Filter on a node property
WHERE m.title = "Toy Story"

38. // Find a pattern in the database
MATCH (p:Person)-[r:ACTED_IN]->(m:Movie)
// Filter on a node property
WHERE m.title = "Toy Story"
// Choose what to return
RETURN p.name AS actor, r.roles AS roles
Reading from Neo4j

39. // Find a pattern in the database
SQL Equivalent
MATCH (p:Person)-[r:ACTED_IN]->(m:Movie)
FROM/JOIN
// Filter on a node property
WHERE m.title = "Toy Story"
WHERE
// Choose what to return
RETURN p.name AS actor, r.roles AS roles SELECT
Reading from Neo4j

40. // Actors who acted with Tom Hanks also acted in...
MATCH (p:Person)-[r:ACTED_IN]->(m:Movie)
<-[:ACTED_IN]-(p2)-[r2:ACTED_IN]->(m2:Movie)
WHERE p.name = "Tom Hanks"
// Return their name and a list of the movie titles
RETURN p2.name AS actor, collect(m2.title) AS
movies
Reading from Neo4j

42. LOAD CSV WITH HEADERS FROM 'file:///stations.csv' AS row
MERGE (s:Station {id: row.id})
SET s.name = row.name,
s.zone = row.zone,
s.location = point({
latitude: toFloat(row.latitude),
longitude: toFloat(row.longitude)
})
Going Underground

43. LOAD CSV WITH HEADERS FROM 'file:///lines.csv' AS row
MERGE (l:Line {id: row.line})
SET l += row {
.name,
.colour,
.stripe
}
Going Underground

44. Going Underground
LOAD CSV WITH HEADERS FROM 'file:///stops.csv' AS row
MATCH (s1:Station {id: row.station1})
MATCH (s2:Station {id: row.station2})
MATCH (l:Line {id: row.line})
CALL apoc.create.relationship(
s1,
toUpper(replace(l.name, ' ', '_')), {}, s2
) YIELD rel

47. MATCH (start:Station {name: "Liverpool Street"})
MATCH (end:Station {name: "Kensington (Olympia)"})
MATCH path = allShortestPaths((start)-[*..99]-(end))
WHERE all(r in relationships(path) WHERE not r:`WATERLOO_&_CITY_LINE`)
AND all(n in nodes(path) WHERE not r:Busy)
RETURN path

48. ● Completely Free
● Hands-on Courses
teaching Neo4j Fundamentals, Cypher,
Drivers and Graph Data Science
● Curated Learning Paths
catering for everyone from beginners to
experts
● Free Certifications
graphacademy.neo4j.com
Learn more with