An introduction to Neo4j and graph databases, including some use cases. Presentation from JFokus 2011.

1. Neo4j
- or, why graph dbs are teh
AWESOME!!!11
oh, and also... USE CASES!!!
#neo4j
Emil Eifrem @emileifrem
Neo Technology emil@neotechnology.com

2. What's the plan?
An intro to graph databases and Neo4j
Brief review of some use cases
Conclusion and Q&A

3. Graph DBs
& Neo4j intro

4. The Graph DB model: representation
Core abstractions:
name = “Emil”
Nodes
age = 29
sex = “yes”
Relationships between nodes
Properties on both 1 2
type = KNOWS
time = 4 years 3
type = car
vendor = “SAAB”
model = “95 Aero”

5. Example: The Matrix
name = “The Architect”
name = “Morpheus”
rank = “Captain”
name = “Thomas Anderson”
occupation = “Total badass” 42
age = 29
disclosure = public
KNOWS KNOWS CODED_BY
KNO
1 7 3 W S
KN
13
S
OW name = “Cypher”
KNOW
S last name = “Reagan”
name = “Agent Smith”
disclosure = secret version = 1.0b
age = 3 days age = 6 months language = C++
2
name = “Trinity”

6. Code (1): Building a node space
GraphDatabaseService graphDb = ... // Get factory
// Create Thomas 'Neo' Anderson
Node mrAnderson = graphDb.createNode();
mrAnderson.setProperty( "name", "Thomas Anderson" );
mrAnderson.setProperty( "age", 29 );
// Create Morpheus
Node morpheus = graphDb.createNode();
morpheus.setProperty( "name", "Morpheus" );
morpheus.setProperty( "rank", "Captain" );
morpheus.setProperty( "occupation", "Total bad ass" );
// Create a relationship representing that they know each other
mrAnderson.createRelationshipTo( morpheus, RelTypes.KNOWS );
// ...create Trinity, Cypher, Agent Smith, Architect similarly

7. Code (1): Building a node space
GraphDatabaseService graphDb = ... // Get factory
Transaction tx = graphDb.beginTx();
// Create Thomas 'Neo' Anderson
Node mrAnderson = graphDb.createNode();
mrAnderson.setProperty( "name", "Thomas Anderson" );
mrAnderson.setProperty( "age", 29 );
// Create Morpheus
Node morpheus = graphDb.createNode();
morpheus.setProperty( "name", "Morpheus" );
morpheus.setProperty( "rank", "Captain" );
morpheus.setProperty( "occupation", "Total bad ass" );
// Create a relationship representing that they know each other
mrAnderson.createRelationshipTo( morpheus, RelTypes.KNOWS );
// ...create Trinity, Cypher, Agent Smith, Architect similarly
tx.commit();

8. Code (1b): Def ning RelationshipTypes
i
// In package org.neo4j.graphdb
public interface RelationshipType
{
String name();
}
// In package org.yourdomain.yourapp
// Example on how to roll dynamic RelationshipTypes
class MyDynamicRelType implements RelationshipType
{
private final String name;
MyDynamicRelType( String name ){ this.name = name; }
public String name() { return this.name; }
}
// Example on how to kick it, static-RelationshipType-like
enum MyStaticRelTypes implements RelationshipType
{
KNOWS,
WORKS_FOR,
}

9. Whiteboard friendly
owns
Björn Big Car
build drives
DayCare

10. The Graph DB model: traversal
Traverser framework for
high-performance traversing name = “Emil”
age = 31
across the node space sex = “yes”
1 2
type = KNOWS
time = 4 years 3
type = car
vendor = “SAAB”
model = “95 Aero”

11. Example: Mr Anderson’s friends
name = “The Architect”
name = “Morpheus”
rank = “Captain”
name = “Thomas Anderson”
occupation = “Total badass” 42
age = 29
disclosure = public
KNOWS KNOWS CODED_BY
KNO
1 7 3 W S
KN
13
S
OW name = “Cypher”
KNOW
S last name = “Reagan”
name = “Agent Smith”
disclosure = secret version = 1.0b
age = 3 days age = 6 months language = C++
2
name = “Trinity”

12. Code (2): Traversing a node space
// Instantiate a traverser that returns Mr Anderson's friends
Traverser friendsTraverser = mrAnderson.traverse(
Traverser.Order.BREADTH_FIRST,
StopEvaluator.END_OF_GRAPH,
ReturnableEvaluator.ALL_BUT_START_NODE,
RelTypes.KNOWS,
Direction.OUTGOING );
// Traverse the node space and print out the result
System.out.println( "Mr Anderson's friends:" );
for ( Node friend : friendsTraverser )
{
System.out.printf( "At depth %d => %s%n",
friendsTraverser.currentPosition().getDepth(),
friend.getProperty( "name" ) );
}

13. name = “The Architect”
name = “Morpheus”
rank = “Captain”
name = “Thomas Anderson”
occupation = “Total badass” 42
age = 29
disclosure = public
KNOWS KNOWS CODED_BY
KNO
1 7 3 W S
KN 13
S
OW name = “Cypher”
KNOW
S last name = “Reagan”
name = “Agent Smith”
disclosure = secret version = 1.0b
age = 3 days age = 6 months language = C++
2
name = “Trinity”
$ bin/start-neo-example
Mr Anderson's friends:
At depth 1 => Morpheus
friendsTraverser = mrAnderson.traverse(
Traverser.Order.BREADTH_FIRST, At depth 1 => Trinity
StopEvaluator.END_OF_GRAPH, At depth 2 => Cypher
ReturnableEvaluator.ALL_BUT_START_NODE,
RelTypes.KNOWS,
At depth 3 => Agent Smith
Direction.OUTGOING ); $

14. Example: Friends in love?
name = “The Architect”
name = “Morpheus”
rank = “Captain”
name = “Thomas Anderson”
occupation = “Total badass” 42
age = 29
disclosure = public
KNOWS KNOWS CODED_BY
KNO
1 7 3 W S
KN 13
S
KNOW
OW name = “Cypher”
S last name = “Reagan”
name = “Agent Smith”
LO disclosure = secret version = 1.0b
VE age = 6 months language = C++
S
2
name = “Trinity”

15. Code (3a): Custom traverser
// Create a traverser that returns all “friends in love”
Traverser loveTraverser = mrAnderson.traverse(
Traverser.Order.BREADTH_FIRST,
StopEvaluator.END_OF_GRAPH,
new ReturnableEvaluator()
{
public boolean isReturnableNode( TraversalPosition pos )
{
return pos.currentNode().hasRelationship(
RelTypes.LOVES, Direction.OUTGOING );
}
},
RelTypes.KNOWS,
Direction.OUTGOING );

16. Code (3a): Custom traverser
// Traverse the node space and print out the result
System.out.println( "Who’s a lover?" );
for ( Node person : loveTraverser )
{
System.out.printf( "At depth %d => %s%n",
loveTraverser.currentPosition().getDepth(),
person.getProperty( "name" ) );
}

17. name = “The Architect”
name = “Morpheus”
rank = “Captain”
name = “Thomas Anderson”
occupation = “Total badass” 42
age = 29
disclosure = public
KNOWS KNOWS KNO CODED_BY
1 7 3 W S
KN 13
S
name = “Cypher”
KNOW
OW
S last name = “Reagan”
name = “Agent Smith”
LO disclosure = secret version = 1.0b
VE age = 6 months language = C++
S
2
name = “Trinity”
$ bin/start-neo-example
new ReturnableEvaluator()
Who’s a lover?
{
public boolean isReturnableNode(
TraversalPosition pos)
At depth 1 => Trinity
{ $
return pos.currentNode().
hasRelationship( RelTypes.LOVES,
Direction.OUTGOING );
}
},

18. Bonus code: domain model
How do you implement your domain model?
Use the delegator pattern, i.e. every domain entity wraps a
Neo4j primitive:
// In package org.yourdomain.yourapp
class PersonImpl implements Person
{
private final Node underlyingNode;
PersonImpl( Node node ){ this.underlyingNode = node; }
public String getName()
{
return (String) this.underlyingNode.getProperty( "name" );
}
public void setName( String name )
{
this.underlyingNode.setProperty( "name", name );
}
}

19. Domain layer frameworks
Qi4j (www.qi4j.org)
Framework for doing DDD in pure Java5
Def nes Entities / Associations / Properties
i
Sound familiar? Nodes / Rel’s / Properties!
Neo4j is an “EntityStore” backend
Jo4neo (http://code.google.com/p/jo4neo)
Annotation driven
Weaves Neo4j-backed persistence into domain objects at runtime
S pring D a ta G ra ph (http://www.springsource.org/spring-data)
Collaboration with SpringSource
Annotation driven, AspectJ based

20. Neo4j system characteristics
Disk-based
Native graph storage engine with custom binary on-disk
format
Transactional
JTA/JTS, XA, 2PC, Tx recovery, deadlock detection,
MVCC, etc
Scales up
Many billions of nodes/rels/props on single JVM
Robust
7+ years in 24/7 production

21. M'kay... but what are some
use cases?

22. Social data (customer: e.g. EU largest social network)
name = “Marcy Runkle”
name = “Hank”
last_name = “Moody”
name = “Mike”
age = 42 42
age = 29 S
W
NO
disclosure = public
K
KNOWS KNOWS KNO
1 7 3 W S
KN
13
S
OW name = “Charlie”
KNOW
S last_name = “Runkle”
name = “Dani”
last_name = “California”
age = 3 days age = 27
2
name = “Karen”

23. Just a social graph?

24. Spatial data (customer: large telecom company)
name = ...
name = “The Tavern”
lat = 1295238237
name = “Omni Hotel”
long = 234823492 42
lat = 3492848
long = 283823423 length = 7 miles AD
RO
ROAD ROAD ROO
1 7 3 OAD
RO
13
AD name = ...
ROAD
lat, long = ...
name = “Swedland”
lat = 23410349
length = 3 miles long = 2342348852
2
name = ...

25. Social? Spatial? … Social AND spatial!

26. Social AND spatial data (customer: LBS)
name = “Peter”
name = “The Tavern”
lat = 1295238237
name = “Omni Hotel”
long = 234823492 42
lat = 3492848 S
W
NO
long = 283823423 weight = 10
K
ROAD LIKES SIBL
1 7 3 IN G
RO
13
AD name = “Emil”
ROAD
beer_qual = expert
name = “Maria”
age = 30
length = 3 miles beer_qual = non-existant
2
name = ...

27. Financial data (customer: international bank)
name = ...
name = “The Tavern”
lat = 1295238237
long = 234823492 42
name = “Mr Godfather” AW
karma = veeeery-low
HDR
cash = more-than-you amount = $1000
IT
W
OWNS TRANSFER WIT
1 7 3 HDR
AW
13
S FE R
DE name = “Emil”
P OS cash = always-too-li'l
IT TRAN
title = “ATM @ Wall St”
id = 230918484233
amount = $1000 cash_left = 384204
2
name = ...

28. Cute. But what about performance?
name = ...
name = “The Tavern”
lat = 1295238237
long = 234823492 42
name = “Mr Godfather” AW
karma = veeeery-low
HDR
cash = more-than-you amount = $1000
IT
W
WITHDRAW TRANSFER WIT
1 7 3 HDR
AW
13
S FE R
DE name = “Emil”
P OS cash = always-too-li'l
IT TRAN
title = “ATM @ Wall St”
id = 230918484233
amount = $1000 cash_left = 384204
2
name = ...
pathExists(a, b, 5)
# nodes query time
Relational database (MySQL) 1 000 2 000 ms
Graph database (Neo4j) 1 000 2 ms
Graph database (Neo4j) 1 000 000 2 ms

29. How ego are you? (aka other impls?)
Franz’ A lle g roG ra ph (http://agraph.franz.com)
Proprietary, Lisp, RDF-oriented but real graphdb
Sones g ra phD B (http://sones.com)
.NET, open source version available
Twitter's Flo c k D B (http://github.com/twitter/flockdb)
Twitter's graph database for large and shallow graphs
Sparsity Technologies D ex (http://sparsitytechnologies.com)
New on the scene, spun out of Spanish university
Objectivity I nfiniteG ra ph (http://infinitegraph.com)
Graph db on-top-of OODB

30. Conclusion
Graphs && Neo4j => teh awesome!
Available NOW under AGPLv3 / commercial license
AGPLv3: “if you’re open source, we’re open source”
If you have proprietary software? Must buy a commercial
license
But the first one is free!
Download
http://neo4j.org
Feedback
http://lists.neo4j.org

32. T he N eo 4j tea m
is hiring !
Do you see the Matrix?
Apply now.

33. Questions?
Image credit: lost again! Sorry :(

34. http://neotechnology.com