1. Cédric Fauvet
Cedric.fauvet@neotechnology.com
Twitter Francophone: @Neo4jFr
1
Confidential - Neo Technology, Inc.
New opportunities for connected data :
Neo4j the graph database

2. Agenda
• The gaph theory
• About Neo Technology
• Uses cases
• Vision du marché
• The Neo4j Technology
• Cypher the Neo4j’s « SQL »

3. The graph theory
An 840 : The horeseman’s problem
The Arab mathematician and chess master
al-Adli ar-Rumi solved the problem.

4. The graph theory
An 1735 The Königsberg’s 7 bridges
problem
How to pass through the bridges only once ?
Leonhard Euler
Swiss mathematician

5. The graph theory
2013: Today’s questions
• Collaboration
• Configuration management
• Geo mapping
• Molecule’s Interaction (Biology)
• Impact analysis
• Master Data Management
• Product management
• Recommendation
• Social

6. Agenda
• The gaph theory
• About Neo Technology
• Uses cases
• Vision du marché
• The Neo4j Technology
• Cypher the Neo4j’s « SQL »

7. Neo Technology (Neo4j) Corporate Overview
• Neo4j founded 2000
• Headquartered in Palo Alto, California
• Engineering headquarter in Malmö, Sweden
• Employees based in France, Germany, UK, Sweden, US, and Malaysia
• 24/7 support on global basis
• 100,000+ users
• F500 customers such as Adobe, Cisco, Deutsche Telecom, Telenor,
Deutsche Post, SFR, Lockheed Martin, and others
• SI partners such as Accenture and dozens of local SI boutiques
• Technology partners such as VMware, Informatica and Microsoft
• Leader in the Graph Database arena
• Mission: Help the world to make sense of data

8. Agenda
• The gaph theory
• About Neo Technology
• Uses cases
• Vision du marché
• The Neo4j Technology
• Cypher the Neo4j’s « SQL »

9. Société
- Worldwide company
- 45 millions users, + 30 000 each days.
- Owner of the social networks
ApnaCircle (Inde) and Tianji (Chine)
Problème
Viadeo, integrated Neo4j as their backend database, to
store all of their users and relationships. When their
network expanded to a level that their traditional MySQL
database couldn’t handle, Viadeo experienced
performance and storage issues that would not perform
at the rate the
company was growing.
Etude de cas: Réseau social
Bénéfices & time frame
- Real time
recomendation with
Neo4j.
- Project timeframe
= 8 weeks
Solution
Integrating Neo4j, Viadeo has highly accelerated their
system in two ways. Neo4j increased Viadeo’s performance
by requiring less storage space andless time to restructure
the graph.

10. 10
Company
- Worldwide leader in networking for the Internet
Solution
- Clustered Neo4j Enterprise architecture
- Part of a larger infrastructure solution
- Multi-region AWS deployment
- Neo4j selected in competition with custom solution
and Oracle
Benefits & time frame
- Highly flexible data analysis
- Sub-second results for large, densely-connected datasets
- User experience - competitive advantage
- 12 month project
Problem definition
- Massive amounts of data tied to members, user
groups, member content, etc. all interconnected
- Need to infer collaborative relationships based on
user-generated content
Case study: Web/ISV - social collaboration
Adobe

11. 11
Company
- Leading telco provider in the Nordics
Solution
- Neo4j Enterprise solution
- Embedded + HA
- Replacing 10 yr-old Oracle, Berkeley DB and a
mainframe environment
Problem definition
- Need: Reliable access control administration system
for 5mio customers, subscriptions and agreements
- Complex dependencies between groups, companies,
individuals, accounts, products, subscriptions,
services and agreements
- Broad and deep graphs (master customers with
1000s of customers, subscriptions & agreements)
Case study: Telco
Telenor
Benefits & time frame
- Flexible and dynamic architecture
- Exceptional performance
-Low cost compared to alternatives
-Extensible data model supports new applications and
features

12. 12
Company
-World wide leader in network infrastructure
-Large sales organization
Solution
-2x Highly Available Neo4j clusters
-One live cluster and one backup / hot spare cluster
at a different datacenter
-Total: 6 Embedded Enterprise Neo4j DBs
Benefits & timeframe
-Real time overview of sales accounts and owners
-The ability to model complex rules for account ownership
-Direct commissioning computation through the entire sales
organization
->12 month development and rollout
Problem definition
-Intricate rules governing ownership of sales accounts
-Complex rules for sales commissions
-Queries complicated to structure with RDBMS
-Oracle performance not good enough for online
account management
Case study: Sales account management
Cisco

13. Use case – What’s in common ?
Alice
ACME
ACME
EMEA
Bob
Retail Co.
FooBar Inc.
Sales Rep
Sales Rep
Worked For
Worked For
Sold To

14. Use case – What’s a best path ?
Retail Co.
Bob
ACME
Steve
Jane
Liza
Pauline
William
Sales Rep
VP
CMO
Sales Rep
VP

15. Use case : Pattern matching
Fraud detection

16. Correspondance
Fraud detection

17. Pas de correspondance
Fraud detection

18. Graph navigation
Impact analysis

19. Start node
Impact analysis

20. Follow the relationships
Impact analysis

21. Evaluate each node
Impact analysis

22. Agenda
• The gaph theory
• About Neo Technology
• Uses cases
• Vision du marché
• The Neo4j Technology
• Cypher the Neo4j’s « SQL »

23. Trend 1:Exponential
growth of data
0
250
500
750
1000
2007 2008 2009 2010
Exabytes of new unique digital information

25. size * connectivity = complexity

27. Agenda
• The gaph theory
• About Neo Technology
• Uses cases
• Vision du marché
• The Neo4j Technology
• Cypher the Neo4j’s « SQL »

28. Neo4j
Tackles complex data:
– Large
– Densely-connected
– Semi-structured

29. Neo4j characteristics
• Fully ACID
– Including XA-compliant distributed two-phase commits
• High Availability / Read Scaling through master-slave
replication with master failover
• In-memory speeds with warm caches while
maintaining full ACID
• Cypher query language and Java APIs

30. Caractéristiques de Neo4j
• Transactions Full ACID
– XA-compliant distributed two-phase commits
• Haute disponibilité / Scalabilité*
– master-slave réplication avec master Fail-over
– * Lecture
• Hautes performance en mémoire
– Caches évolués full ACID
• Langage des requêtes
– Cypher
– Java APIs
– JDBC
– Rest API
– Ruby

31. Agenda
• The gaph theory
• About Neo Technology
• Uses cases
• Vision du marché
• The Neo4j Technology
• Cypher the Neo4j’s « SQL »

32. () --> ()
Cypher the Neo4j’s « SQL »
Based on ACSII-Art

33. (A) --> (B)
A B
Cypher the Neo4j’s « SQL »
Each node have a identifier

34. A -[:LOVES]-> B
LOVES
A B
Cypher the Neo4j’s « SQL »
Relationship

35. A --> B --> C
A B C
Cypher the Neo4j’s « SQL »
You can traverse the graph

36. A -[*]-> B
A B
A B
A B
Cypher the Neo4j’s « SQL »
You can dynamically traverse the graph

37. Cypher the Neo4j’s « SQL »
The friend of friend query
START john=node:node_auto_index(name = 'John')
MATCH john-[:friend]->()-[:friend]->fof
RETURN john, fof

38. Thank you
Let’s move forward together !
Cédric Fauvet Your contact in France and switzerland
E-mail : Cedric.fauvet@neotechnology.com
French speaking Twitter : @Neo4jFr
French speaking community : meetup.com/graphdb-france