Andrew Frei, Neo4j EInführung in Neo4j und Graphdatenbanken

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2. Einführung in Neo4j
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• Die primären Anwendungsfälle von Graphdatenbanken
• Die ‚Secret Sauce‘ von Neo4j, die diese möglich machen
• Die Visualisierung von Graphen
• Einfach mit Neo4j loslegen, aber wie?

3. Who am I … Andrew Frei
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(Andrew) -[:LIVES_NEAR]->(Zurich)
(Andrew) -[:HAS_SHOESIZE]-> (47)
(Andrew) -[:IS_TODAYS]-> (host)
(Andrew) -[:LOVES]-> (Neo4j)
(Andrew) -[:LOVES_SELLING]-> (Neo4j)
Tagline: Supporting Companies to 'Connect the Dots' with Graph Databases & Analytics
Contact: linkedin.com/in/andrew-frei/ and andrew.frei@neo4j.com

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The way we use to work; look at it…..

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Swap Glasses…

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Look at it again, now as a graph

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The Graph Problem Problem
Many organizations don’t realize that they have a graph problem.

8. Labeled Property Graph Model
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• Nodes – Represent objects
in the graph

9. DRIVES
Labeled Property Graph Model
MARRIED TO
LIVES WITH
OW
NS
99
• Nodes – Represent objects
in the graph
• Relationship – Relate
nodes by type and direction

10. DRIVES
name: “Dan”
born: May 29, 1970
twitter: “@dan”
name: “Ann”
born: Dec 5, 1975
since:
Jan 10, 2011
brand: “Volvo”
model: “V70”
Latitude: 37.5629900°
Longitude: -122.3255300°
Labeled Property Graph Model
MARRIED TO
LIVES WITH
OW
NS
1010
• Nodes – Represent objects
in the graph
• Relationship – Relate
nodes by type and direction
• Property – Name-value
pairs that can go on nodes
and relationships

11. CAR
DRIVES
name: “Dan”
born: May 29, 1970
twitter: “@dan”
name: “Ann”
born: Dec 5, 1975
since:
Jan 10, 2011
brand: “Volvo”
model: “V70”
Latitude: 37.5629900°
Longitude: -122.3255300°
Labeled Property Graph Model
MARRIED TO
LIVES WITH
OW
NS
PERSON PERSON
1111
• Nodes – Represent objects
in the graph
• Relationship – Relate
nodes by type and direction
• Property – Name-value
pairs that can go on nodes
and relationships
• Label – Group nodes and
shape the domain

12. The Whiteboard Model Is the Physical Model

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Industries - Use Cases
Telco & Utilities
Banks &
Insurers, Gov’t
Media, Software & IT
companies
Life Sciences &
Pharma
Manufacturing
& Logistics
eCommerce, other
industries

14. Connected Data - Use Cases
Network &
IT Operations
Fraud
Detection
Identity & Access
Management
Knowledge
Graph
Master Data
Management
Real-Time
Recommendations

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16. Adobe Behance
Social Network of 10M
Graphic Artists
Background
● Social network of 10M graphic artists
● Peer-to-peer evaluation of art and works-in-progress
● Job sourcing site for creatives
● Massive, millions of updates (reads & writes) to Activity Feed
● 150 Mongos to 48 Cassandras to 3 Neo4j’s!
Business Problem
● Artists subscribe, appreciate and curate “galleries” of works of their own
and from other artists
● Activities Feed is how everyone receives updates
● 1st implementation was 150 MongoDB instances
● 2nd implementation shrunk to 48 Cassandras, but it was still too slow and
required heavy IT overhead
Solution and Benefits
● 3rd implementation shrunk to 3 Neo4j instances
● Saved over $500k in annual AWS fees
● Reduced data footprint from 50TB to 40GB
● Significantly easier to introduce new features like, “New projects in your
Network”

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18. Dun & Bradstreet
Neo4j for Tracking Beneficial
Ownership
Background
● Regulations and requirements around beneficial
ownership
● Needed to let B2B clients book new business promptly
via accelerated due diligence investigations
Business Problem
● Investigations call for highly trained staff, and this activity is
hard to scale. A single request might tie up key people for
10-15 days, resulting in lost revenue
Solution and Benefits
● Use Neo4j to quickly query historic relationships between
business owners and companies
● Query responses take milliseconds versus days of skilled
manual research

19. ICIJ Panama Papers
Fraud Detection /
Graph-Based Search
Background
● International investigative team specializing in
cross-border crime, corruption and accountability of
power
Business Problem
● Find relationships between people, accounts, shell companies
and offshore accounts
● Biggest “Snowden-Style” document leak ever; 11.5 million
documents, 2.6TB of data
Solution and Benefits
● Pulitzer Prize winning investigation resulted in robust
coverage of fraud and corruption
● PM of Iceland resigned, exposed Putin, Prime Ministers,
gangsters, celebrities (Messi) - Trials are ongoing

20. How Neo4j Fits — Common Architecture Patterns
From Disparate Silos
To Cross-Silo Connections
From Tabular Data
To Connected Data
From Data Lake Analytics
to Real-Time Operations

21. for Graph Data Science™
Neo4j Graph Data
Science Library
Scalable Graph Algorithms
& Analytics Workspace
Native Graph
Creation & Persistence
Neo4j
Database
Visual Graph Exploration
& Prototyping
Neo4j
Bloom
Practical Integrated Intuitive

22. • Degree Centrality
• Closeness Centrality
• Harmonic Centrality
• Betweenness Centrality & Approx.
• PageRank
• Personalized PageRank
• ArticleRank
• Eigenvector Centrality
• Triangle Count
• Clustering Coefficients
• Connected Components (Union Find)
• Strongly Connected Components
• Label Propagation
• Louvain Modularity
• Balanced Triad (identification)
50+ Graph Algorithms in Neo4j
• Shortest Path
• Single-Source Shortest Path
• All Pairs Shortest Path
• A* Shortest Path
• Yen’s K Shortest Path
• Minimum Weight Spanning Tree
• K-Spanning Tree (MST)
• Random Walk
• Breadth & Depth First Search
• Triangle Count
• Local Clustering Coefficient
• Connected Components (Union Find)
• Strongly Connected Components
• Label Propagation
• Louvain Modularity
• K-1 Coloring
• Modularity Optimization
• Euclidean Distance
• Cosine Similarity
• Node Similarity (Jaccard)
• Overlap Similarity
• Pearson Similarity
• Approximate KNN
Pathfinding
& Search
Centrality /
Importance
Community
Detection
Similarity
Link
Prediction
• Adamic Adar
• Common Neighbors
• Preferential Attachment
• Resource Allocations
• Same Community
• Total Neighbors
... Auxiliary Functions:
• Random
graph generation
• Graph export
• One hot encoding
• Distributions & metrics
Embeddings
• Node2Vec
• Random Projections
• GraphSAGE

23. Mission
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❏ Tom Hanks is getting old(er)...
❏ We can boost his career and put him together with a few new faces. Who do
you recommend? How would you give weight to your recommendation?

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25. Analytics
Tooling
Graph
Transactions
Dev.
& Admin
Graph Analytics &
Data Science
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Applications Business Users
Native Graph Technology for Applications & Analytics
Data Analysts
Data Scientists
Drivers & APIs Discovery & Visualization
Data Integration
Developers
Admins

26. 7/10
20/25
7/10
Top Retail Firms
Top Financial Firms
Top Software Vendors
Anyway You Like It
Neo4j - The Graph Company
The Industry’s Largest Dedicated Investment in Graphs
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Creator of the Property
Graph and Cypher language
at the core of the GQL ISO
project
Thousands of Customers
World-Wide
HQ in Silicon Valley, offices
include London, Munich,
Paris & Malmo
Industry Leaders use Neo4j
On-Prem
DB-as-a-Service
In the Cloud

27. 27 neo4j.com/sandbox

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Q & A

29. Contact details
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Andrew Frei
Sales Manager Switzerland & Austria
Neo4j
linkedin.com/in/andrew-frei/
andrew.frei@neo4j.com
+41 78 793 42 56
www.neo4j.com
Bruno Ungermann
Sales Manager Germany
Neo4j
linkedin.com/in/brunoungermann/
bruno.ungermann@neo4j.com
www.neo4j.com