GraphTour 2020 Amsterdam Michal Bachman, CEO, GraphAware

1. © 2019 GraphAware Ltd. All rights reserved.
Practical Applications of Neo4j 4.0
Neo4j GraphTour 2020 - Amsterdam
Michal Bachman | 04/02/2020
michal@graphaware.com
+44 7714 300 401
www.graphaware.com
@graph_aware
@bachmanm

2. © 2019 GraphAware Ltd. All rights reserved.
Quick Intro
Fine-Grained Security
Multiple Databases
Scalability
Conclusion
Contents
01
#
02
03
04
05

3. © 2019 GraphAware Ltd. All rights reserved.
Quick Introduction

4. © 2019 GraphAware Ltd. All rights reserved.
Fine-Grained Security
for Law Enforcement and Intelligence

5. © 2019 GraphAware Ltd. All rights reserved.
Find Shortest Path
Person Person

6. © 2019 GraphAware Ltd. All rights reserved.
Neo4j 3.x
simple shortest path search
MATCH p=allShortestPaths((p1)-[*]-(p2))
Person
Officer
Person
INVESTIGATES
INVESTIGATES

7. © 2019 GraphAware Ltd. All rights reserved.
Person Person
Neo4j 3.x
More please…
MATCH p=allShortestPaths((p1)-[*]-(p2))

8. © 2019 GraphAware Ltd. All rights reserved.
Neo4j 3.x
Security logic mixed into
queries.
MATCH p=allShortestPaths((p1)-[*]-(p2))
WHERE ALL(x in nodes(p) WHERE NOT x:Secret)
Person
Person
Person
Person
“”
Email
“”
Sms
“”
Sms
C
Call
“”
Sms
F
ROM
FROM
FROM
FRO
M
FROM
TO
TO
TO
TO
TO

9. © 2019 GraphAware Ltd. All rights reserved.
Fine-Grained Security
in Neo4j 4.0

10. © 2019 GraphAware Ltd. All rights reserved.
Neo4j 4.0 - User 1
simple shortest path search
MATCH p=allShortestPaths((p1)-[*]-(p2))
Person
Officer
Person
INVESTIGATES
INVESTIGATES

11. © 2019 GraphAware Ltd. All rights reserved.
Neo4j 4.0 - User 2
simple shortest path search
MATCH p=allShortestPaths((p1)-[*]-(p2))
Person
Person
Person
Person
“”
Email
“”
Sms
“”
Sms
C
Call
“”
Sms
F
ROM
FROM
FROM
FRO
M
FROM
TO
TO
TO
TO
TO

12. © 2019 GraphAware Ltd. All rights reserved.
Neo4j 4.0 - User 3
simple shortest path search
MATCH p=allShortestPaths((p1)-[*]-(p2))
Person
Officer
Person
INVESTIGATES
INVESTIGATES

13. © 2019 GraphAware Ltd. All rights reserved.
Fine-Grained Security
for <insert your use case>

14. © 2019 GraphAware Ltd. All rights reserved.
Multiple Databases
for Multi-Tenancy and Cleaner Graphs

15. © 2019 GraphAware Ltd. All rights reserved.
Multiple Databases
multiple logical graphs

16. © 2019 GraphAware Ltd. All rights reserved.

17. © 2019 GraphAware Ltd. All rights reserved.

18. © 2019 GraphAware Ltd. All rights reserved.
https://www.shutterstock.com/image-photo/hand-holding-interface-social-media-concept-173103695?src=library

19. © 2019 GraphAware Ltd. All rights reserved.

20. © 2019 GraphAware Ltd. All rights reserved.

21. © 2019 GraphAware Ltd. All rights reserved.
Multiple Databases
graphs of different qualities

22. © 2019 GraphAware Ltd. All rights reserved.

23. © 2019 GraphAware Ltd. All rights reserved.

24. © 2019 GraphAware Ltd. All rights reserved.
Multiple Databases
auditing

25. © 2019 GraphAware Ltd. All rights reserved.

26. © 2019 GraphAware Ltd. All rights reserved.
Multiple Databases
for Multi-Tenancy and Cleaner Graphs

27. © 2019 GraphAware Ltd. All rights reserved.
Scalability
for Graph-Powered Machine Learning

28. © 2019 GraphAware Ltd. All rights reserved.
Graphs are the underpinning technology of
all modern machine learning and AI applications.
The results of machine learning are brought
back into your central graph database –
the brain for your organization.”
Alessandro Negro
Chief Scientist, GraphAware
“

29. © 2019 GraphAware Ltd. All rights reserved.

30. © 2019 GraphAware Ltd. All rights reserved.
INSIGHTS
DELIVERY
M
A
C
H
INELEARNING
ANALYSIS
API
ENRICH
DATA
Data
External
Knowledge
NATURALLANGUAGE
PR
O
CESSING
ENRICHMENT
Business
Systems
& Customer
Engagement
UX CX
INGESTION api

31. © 2019 GraphAware Ltd. All rights reserved.
Scalability
for Graph-Powered Machine Learning

32. © 2019 GraphAware Ltd. All rights reserved.
Conclusion

33. © 2019 GraphAware Ltd. All rights reserved.
Thank you
For more information please contact:
Michal Bachman | 04/02/2020
michal@graphaware.com
+44 7714 300 401
www.graphaware.com
@graph_aware
@bachmanm