Slides from Rik Van Bruggen's talk on Exploiting Big Data with Graphs at the 18th Big Data London meetup.

1. Exploi'ng
Big
Data
with
Graphs
Rik
Van
Bruggen
Regional
Director,
Neo
Technology
@rvanbruggen

2. Roadmap
• The
Rela'onal
Crossroads
• The
NOSQL
answer
– The
volume
answer
– The
complexity
answer
• Exploi'ng
Complexity
with
Graphs
• Ques'ons
/
Answers

5. The
“Big
Data”
problem
The
big
“Data
Problem”

6. NOT
ONLY
SQL

7. The
“Big
Data”
problem

8. hLp://www.flickr.com/photos/crazyneighborlady/355232758/

9. hLp://gallery.nen.gov.uk/image82582-­‐.html

10. hLp://www.xtranormal.com/watch/6995033/mongo-­‐db-­‐is-­‐web-­‐scale

11. Large
amounts
of
simple
data

12. Aggregate-­‐Oriented
Data
hLp://mar'nfowler.com/bliki/AggregateOrientedDatabase.html
“There is a significant downside - the whole approach works really well
when data access is aligned with the aggregates, but what if you want to
look at the data in a different way? Order entry naturally stores orders as
aggregates, but analyzing product sales cuts across the aggregate structure.
The advantage of not using an aggregate structure in the database is that it
allows you to slice and dice your data different ways for different
audiences.
This is why aggregate-oriented stores talk so much about map-reduce.”

13. BUT
HOW
TO
EXPLOIT
BIG
DATA
in
the
face
of
COMPLEXITY?

14. The
big
“Data
Problem”

15. complexity = f(size, connectedness, variability)

17. hLp://en.wikipedia.org/wiki/File:Leonhard_Euler_2.jpg
Meet
Leonhard
Euler
• Swiss
mathema'cian
• Inventor
of
Graph
Theory
(1736)

18. Königsberg
(Prussia)
-­‐
1736

19. A
B
D
C

20. A
B
D
C
1"
2"
3"
4"
7"
6"
5"

21. hLp://www.bbc.co.uk/london/travel/downloads/tube_map.html

22. Property
graphs
• Property
graph
model:
– Nodes
with
proper'es
– Named,
directed
rela'onships
with
proper'es
– Rela'onships
have
exactly
one
start
and
end
node
• Which
may
be
the
same
node

23. Property
Graph
Model

24. Property
graphs
are
very
whiteboard-­‐friendly

25. Exploi'ng
data:
Cypher
query
language
• Declara've
graph
paLern
matching
language
– “SQL
for
graphs”
– Columnar
results
• Supports
graph
matching
commands
and
queries
– Find
me
stuff
like
this…
– Aggrega'on,
ordering
and
limit,
etc.

26. Matching
paLerns

27. Pathfinding

28. Logis'cs

29. En'tlements

30. Impact

31. BIG
INSIGHTS
FROM
COMPLEX
DATA

32. The
“Big
Data”
problem
The
big
“Data
Problem”

33. Free
O’Reilly
eBook!
Visit:
hLp://GraphDatabases.com
Ian Robinson,
Jim Webber & Emil Eifrem
Graph
Databases
h
Com
plim
ents
ofNeo
Technology

34. Thanks
for
listening
Neo4j:
hIp://neo4j.org
Me:
@rvanbruggen
,
rik[at]neotechnology[dot]com