Introduction to neo4j and graph databases in generally - looking at what neo4j is, why we should use it, the Cypher query language and the wider ecosystem.

1. G R A P H DATA B A S ES

2. W H O A M I ?
• David Simons
• @SwamWithTurtles
• github.com/
SwamWithTurtles
• Technical Lead at Softwire
and part-time hacker
• Statistician in a past life

3. G ra p h i ca l M o d e l l i n g
N e o 4 J : T h e W h at A n d W h y ?
“ Cy p h e r ” Q u e ry La n g u a g e
Le t ’s S e e I t A ct i o n !
T h e G ra p h i n g Eco s y ste m

4. G ra p h i ca l M o d e l l i n g
N e o 4 J : T h e W h at A n d W h y ?
“ Cy p h e r ” Q u e ry La n g u a g e
Le t ’s S e e I t A ct i o n !
T h e G ra p h i n g Eco s y ste m

5. W H AT I S A G R A P H ?
Taken from Jim Webber’s Dr. Who Dataset

6. W H AT I S A G R A P H ?
{ (V, E) : V = [n], E ⊆ V(2) }

7. W H AT I S A G R A P H ?
{ (V, E) : V = [n], E ⊆ V(2) }
Made up of two parts,
“V” and “E”

8. W H AT I S A G R A P H ?
{ (V, E) : V = [n], E ⊆ V(2) }
V is a set of n items

9. W H AT I S A G R A P H ?
Vertex Set

10. W H AT I S A G R A P H ?
{ (V, E) : V = [n], E ⊆ V(2) }
E is made up of pairs
of elements of V
(Ordered and
not necessarily distinct)

11. W H AT I S A G R A P H ?
Edge Set

12. G I V I N G R E A L
W O R L D
M E A N I N G S T O V
A N D E
W H A T I S G R A P H I C A L
M O D E L L I N G ?

13. B R I D G E S AT K Ö N I G S B E R G

14. B R I D G E S AT K Ö N I G S B E R G
V =
bits of land
E =
bridges

15. K E V I N B A C O N
S I X D E G R E E S O F …

20. T H E R E I S N O O P E N
E L E C T I O N D ATA
T H E P R O B L E M

21. E L E C T I O N D ATA

22. E L E C T I O N D ATA

23. E L E C T I O N D ATA
E =
(e.g.) member of, held in,
stood in…
V =
elections, constituencies,
years, politicians and parties

24. G ra p h i ca l M o d e l l i n g
N e o 4 J : T h e W h at A n d W h y ?
“ Cy p h e r ” Q u e ry La n g u a g e
Le t ’s S e e I t A ct i o n !
T h e G ra p h i n g Eco s y ste m

25. W O R L D ’ S L E A D I N G G R A P H
D B :

26. W H E R E D I D I T
C O M E F R O M ?
• First version 2010, v2 came
out December 2013.

27. "embedded, disk-based, fully transactional Java
persistence engine that stores data structured in
graphs rather than in tables"

28. D ATA S T O R A G E

29. D ATA S T O R A G E

30. D ATA
S T O R A G E
• Nodes and edges are all:
• Stored as first-class
objects on the file
system
• “typed”
• Key-value stores

31. C O M M U N I T Y
E D I T I O N
• Free for hacking around in

32. E N T E R P R I S E
E D I T I O N
• Bespoke Prices, but
includes:
• Higher performance
for concurrent
querying
• Clustering
• Hot backups
• Advanced Monitoring

33. O T H E R G R A P H
D ATA B A S E S
• ArangoDB
• OrientDB
• New: Graph Engine

34. W H AT ’ S
W R O N G W I T H
S Q L ?
B U T…

35. N O T H I N G *

36. N O T H I N G *
*If you use it for
the right job

37. D ATA I N T H E
R E L AT I O N S
• “Joins” are first class
objects in the database
that can be queried at no
additional cost
• Certain queries become
trivial (e.g. Joins)

38. P R O T O T Y P I N G
• Easy to see and work with
data
• Schemaless
• Active community with a
lot of libraries

39. N E O 4 J U S E R S

40. C A S E S T U D I E S
Real-time Recommendations

41. C A S E S T U D I E S
Logistics & Delivery
Organisation

42. C A S E S T U D I E S
Online Dating

43. G ra p h i ca l M o d e l l i n g
N e o 4 J : T h e W h at A n d W h y ?
“ Cy p h e r ” Q u e ry La n g u a g e
Le t ’s S e e I t A ct i o n !
T h e G ra p h i n g Eco s y ste m

44. W H AT I S
C Y P H E R ?
• Neo4j’s own query
language
• Declarative
• Designed to be readable
and easy to learn

45. A S C I I A R T S Y N TA X : N O D E S
(n)
(n:Actor)
(n:Actor {name:”Kevin Bacon”})

46. A S C I I A R T S Y N TA X : E D G E S
-[r:starred_in]->
<-[r:starred_in]-
-[r:starred_in]-

47. A S C I I A R T S Y N TA X : E D G E S
(n:Actor)-[r:starred_in]->(m:Movie)

48. A S C I I A R T S Y N TA X : E D G E S
(n:Actor)-[r:starred_in]->(m:Movie)
<-[r:starred_in]-(a:Actor)

49. M AT C H & R E T U R N
MATCH {pattern} RETURN {variables}

50. M AT C H & R E T U R N
MATCH (n:Actor)-[r:starred_in]->(m:Movie)
RETURN n, r, m

51. M AT C H & R E T U R N
MATCH (n:Actor {name: ”Kevin Bacon”})
-[r:starred_in]->(m:Movie)
RETURN m

52. P E R S I S T E N C E
CREATE (n: Actor {name: “David”})
RETURN n

53. P E R S I S T E N C E
MATCH (m:Movie), (a:Actor {name =“David”})
CREATE (a)-[:starred_in]->(m)
RETURN a, m

54. A G G R E G AT I O N
MATCH (n:Actor)<-[:starred_in]-(m:Movie)
RETURN n, sum(m.revenue)

55. L O A D F R O M C S V
LOAD CSV FROM 'foo.csv' AS line
CREATE (:Actor { name: line[1]})

56. G ra p h i ca l M o d e l l i n g
N e o 4 J : T h e W h at A n d W h y ?
“ Cy p h e r ” Q u e ry La n g u a g e
Le t ’s S e e I t A ct i o n !
T h e G ra p h i n g Eco s y ste m

57. G ra p h i ca l M o d e l l i n g
N e o 4 J : T h e W h at A n d W h y ?
“ Cy p h e r ” Q u e ry La n g u a g e
Le t ’s S e e I t A ct i o n !
T h e G ra p h i n g Eco s y ste m

58. D I F F E R E N T
L A N G U A G E
S U P P O R T
• Java
• Spring Data for full
ORM
• Hibernate OGM
• Embedded Java API
• Kundera

59. D I F F E R E N T
L A N G U A G E
S U P P O R T
• .NET - Neo4jClient
• JavaScript - Seraph.js,
node-neo4j
• Clojure - Neocons
• Haskell, Go, PHP and
more…

60. G R A P H E N E D B
• Remote hosting of neo4j
on Heroku, AWS or Azure
• Monitoring, support, back-
ups, scalability

61. V I S U A L I S AT I O N
T O O L S
• Lots of tools out there to
take subgraphs and turn
them into pretty views.

62. V I S U A L I S AT I O N T O O L S : A L C H E M Y J S

63. V I S U A L I S AT I O N T O O L S : L I N K U R I O U S

64. G R A P H A WA R E
• Java libraries that make
developing with graphs
easier:
• “TimeTree”
• “GraphGen”
• “Reco”

65. I N
C O N C L U S I O N …
• Graphs more accurately
model a lot of domains
• Neo4j is a robust and
mature way of storing this
• It’s got a thriving
ecosystem and community
• Go forth and play!

66. A N Y Q U EST I O N S ?
@ Swa m Wi t h Tu rt l e s
s wa m w i t h t u rt l e s . co m