With the introduction of the Neo4j Graph Platform and increased adoption of graph database technology across all industries, now is a better time than ever to get started with graphs. Join us for this introduction to Neo4j and graph databases. We'll discuss the primary use cases for graph databases and explore the properties of Neo4j that make those use cases possible.

1. Neo4j Introduction
Jonny Cheetham
jonny.Cheetham@neo4j.com
Neo4j, London

2. Neo4j is an enterprise-grade native graph platform that enables you to:
• Store, reveal and query data relationships
• Traverse and analyze any levels of depth in real-time
• Add context and connect new data on the fly
Who We Are: Leader in Graph Innovations
• Performance
• ACID Transactions
• Schema-free Agility
• Graph Algorithms
Designed, built and tested natively
for graphs from the start for:
• Developer Productivity
• Hardware Efficiency
• Global Scale
• Graph Adoption
Graph
Transactions
Graph
Analytics
Data Integration
Development
& Admin
Analytics
Tooling
Drivers & APIs Discovery & Visualization
2

3. 720+
7/10
12/25
8/10
53K+
100+
300+
450+
Adoption
Top Retail Firms
Top Financial Firms
Top Software Vendors
Customers Partners
• Creator of the Neo4j Graph Platform
• ~250 employees
• HQ in Silicon Valley, other offices include
London, Munich, Paris and Malmö Sweden
• $80M new funding led by Morgan Stanley &
One Peak. Total $160M from Fidelity,
Sunstone, Conor, Creandum, and
Greenbridge Capital
• Over 15M+ open source downloads &
container pulls
• 325+ enterprise subscription customers
with over half with >$1B in revenue
Ecosystem
Startups in program
Enterprise customers
Partners
Meet up members
Events per year
Industry’s Largest Dedicated Investment in Graphs
Neo4j - The Graph Company
3

4. Networks of People
Knows
Knows
Knows
Knows
Business Processes
Bought
Bought
Viewed
Returned
Bought
Knowledge Networks
Plays
Lives_in
In_sport
Likes
Fan_of
Plays_for
E.g., Risk management, Supply
chain, Payments
E.g., Employees, Customers,
Suppliers, Partners,
Influencers
E.g., Enterprise content,
Domain specific content,
eCommerce content
Data connections are increasing as rapidly as data volumes
The Rise of Connections in Data
Electronic Networks
On-prem & cloud
computing, Cellular,
Telco & Internet, IoT
4

5. 5
Graph Databases are Designed for Connected Data
TRADITIONAL
DATABASES
BIG DATA
TECHNOLOGY
Store and retrieve data Aggregate and filter data Connections in data
Real time storage & retrieval Real-Time Connected Insights
Long running queries
aggregation & filtering
“Our Neo4j solution is literally thousands of times faster
than the prior MySQL solution, with queries that require
10-100 times less code”
Volker Pacher, Senior Developer
Up to
3
Max #
of
hops
1 Millions

6. 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°
Nodes
• Can have Labels to classify nodes
• Labels have native indexes
Relationships
• Relate nodes by type and direction
Properties
• Attributes of Nodes & Relationships
• Stored as Name/Value pairs
• Can have indexes and composite indexes
• Visibility security by user/role
Neo4j Invented the Labeled Property Graph Model
MARRIED TO
LIVES WITH
OW
NS
PERSON PERSON
6

7. Strictly ConfidentialStrictly Confidential
7
Neo4j Is Helping The World To Make Sense of Data
ICIJ used Neo4j to uncover the
world’s largest journalistic leak to
date, The Panama Papers
NASA uses Neo4j for a “Lessons
Learned” database to improve
effectiveness in search missions in
space
Neo4j is used to graph the human
body, map correlations, identify cause
& effect and search for the cure for
cancer
SAVING
DEMOCRACY
MISSION TO
MARS
CURING CANCER

8. Recommendations Dynamic Pricing IoT-applicationsFraud Detection
Real-Time Transaction Applications
Generate and
Protect Revenue
Customer
Engagement
Metadata and Advanced Analytics
Data Lake
Integration
Knowledge
Graphs for AI
Risk
Mitigation
Generate
Actionable Insights
Network
Management
Supply Chain
Efficiency
Identity and Access
Management
Internal Business Processes
Improve Efficiency
and Cut Costs
8
Graph Use Cases by Value Proposition

9. "Neo4j continues to dominate the graph
database market.”
“69% of enterprises have, or are planning
to implement graphs over next 12 months”
October, 2017
“The most widely stated
reason in the survey for
selecting Neo4j was
to drive innovation”
February, 2018
Critical Capabilities for DBMA
“In fact, the rapid rise of Neo4j and other graph
technologies may signal that data
connectedness is indeed a separate paradigm
from the model consolidation happening across
the rest of the NoSQL landscape.”
March, 2018
Analysts See Unique Benefits of Graphs
"Neo4j is the clear market leader in the graph space. It has the
most users, it uses a widely adopted language that is much easier
than Gremlin and in many respects, it has consistently been a lot
more innovative than its competitors.”
“It is the Oracle or SQL Server of the graph database world.”
March, 2019
"Our research suggests that graph databases have the
best chance to survive and thrive as a distinct
category (versus the other NoSQL models) because
connected data applications present serious performance
problems that only a specialized graph DB can solve.”
March, 2019
9

10. Graph Platform & Initiatives
10

11. Graph
Transactions
Graph
Analytics
Data Integration
Development
& Admin
Analytics
Tooling
Drivers & APIs Discovery & Visualization
Developers
Admins
Applications Business Users
Data Analysts
Data Scientists
Enterprise Data Hub
Native Graph Platform: Tools for Many Users
11

12. Collections-Focused
Multi-Model, Documents, Columns
& Simple Tables, Joins
Neo4j is designed for data relationships
Different Paradigms
NoSQL
Relational
DBMS
Neo4j Graph
Platform
Connections-Focused
Focused on
Data Relationships
Development Benefits
Easy model maintenance
Easy query
Deployment Benefits
Ultra high performance
Minimal resource usage
12

13. 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
13

14. Graph & ML Algorithms in Neo4j+35
neo4j.com/
graph-algorithms-
book/
Pathfinding
& Search
Centrality /
Importance
Community
Detection
Link Prediction
Finds optimal paths
or evaluates route availability
and quality
Determines the importance of
distinct nodes in the network
Detects group clustering
or partition options
Evaluates how alike
nodes are
Estimates the likelihood of
nodes forming a future
relationship
Similarity
14

15. Neo4j Bloom
15
• Visualize
• Communicate
• Discover
• Navigate
• Isolate
• Edit
• Share

16. Graph Use Cases
16

17. 17
Real-Time
Recommendations
Fraud
Detection
Network &
IT Operations
Master Data
Management
Knowledge
Graph
Identity & Access
Management
Common Graph Technology Use Cases
AirBnb

18. Business Problem
• Find relationships between people, accounts, shell companies
and offshore accounts
• Journalists are non-technical
• 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 & Pakistan resigned, exposed Putin, Prime
Ministers, gangsters, celebrities (Messi)
• Led to assassination of journalist in Malta
Background
• International Consortium of Investigative Journalists (ICIJ),
small team of data journalists
• International investigative team specializing in cross-border
crime, corruption and accountability of power
• Works regularly with leaks and large datasets
ICIJ Panama Papers INVESTIGATIVE JOURNALISM
Fraud Detection / Knowledge Graph18

19. ACCOUNT
HAS
REGISTE
RED
ADDRESS
PERSON
IS_OFFICER
_OF
PERSON
NAME
STREET
BANK
WITH
LIVES_
AT
LIVES_
AT
NAME
COMPANY
BANK
BAHAMAS
19

20. Bank
US
Account
Person
A
Company
Bank
Bahamas
Address
HAS
REGISTERED
IS_OFFICER_
OF
WITH
LIVES_AT
LIVES_AT
NODE
RELATIONSHIP
Person
B
20

21. Neo4j Customer Deep Dive
21

22. 22
• Record “Cyber Monday” sales
• About 35M daily transactions
• Each transaction is 3-22 hops
• Queries executed in 4ms or less
• Replaced IBM Websphere commerce
• 300M pricing operations per day
• 10x transaction throughput on half the
hardware compared to Oracle
• Replaced Oracle database
• Large postal service with over 500k
employees
• Neo4j routes 7M+ packages daily at peak,
with peaks of 5,000+ routing operations per
second.
Handling Large Graph Work Loads for Enterprises
Real-time promotion
recommendations
Marriott’s Real-time
Pricing Engine
Handling Package
Routing in Real-Time

23. Background
• Largest Cable TV & Internet Provider in US
• 3rd Largest network on the planet
• xFi is consumer experience in 3M houses
• Internet, router, devices, security, voice & telephony
• Transformational customer experience
Business Problem
• Integrate all experience in a smart home
• Create innovative ideas based on cross-platform
and household member preferences
• Add integrated value of xFinity triple play & quad-
play services (internet, VoIP, cable TV & home
security)
Solution and Benefits
• Custom content per household member
• Security reminders (kids are home, garage left open)
• Serves millions of households
• Makes content recommendations based on
occupant, time of day, permissions and preferences
• Has Siri-like voice commands
COMCAST Xfinity xFi TELECOMMUNICATIONS
Smart Home / Internet of Things23
EE Customer since 2016 Q4

24. Thomson Reuters Graph
24
• Data Fusion for Portfolio Managers
• Graph layers

25. Background
• Personal shopping assistant
• Converses with buyer via text, picture and voice
to provide real-time recommendations
• Combines AI and natural language understanding
(NLU) in Neo4j Knowledge Graph
• First of many apps in eBay's AI Platform
Business Problem
• Improve personal context in online shopping
• Transform buyer-provided context into ideal
purchase recommendations over social platforms
• "Feels like talking to a friend"
Solution and Benefits
• 3 developers, 8M nodes, 20M relationships
• Needed high-performance traversals to respond
to live customer requests
• Easy to train new algorithms and grow model
• Generating revenue since launch
eBay for Google Assistant ONLINE RETAIL
Knowledge Graph powers Real-Time Recommendations25
EE Customer since 2016 Q3

26. Background
• Over 7M citizens suffer from Diabetes
• Connecting over 400 researchers
• Incorporates over 50 databases, 100k’s of Excel
workbooks, 30 database of biological samples
• Sought to examine disease from as many angles as
possible.
Business Problem
• Genes are connected by proteins or to metabolites,
and patients are connected with their diets, etc…
• Needed to improve the utilization of immensely
technical data
• Needed to cater to doctors and researchers with
simple navigation, communication and connections
of the graph.
Solution and Benefits
• Dr. Alexander Jarasch, Head of Bioinformatics and
Data Management
• Scientists can conduct parallel research without
asking the same questions or repeating tests
• Built views like a liver sample knowledge graph
DZD - German Center for Diabetes Research
Medical Genomic Research26
EE Customer since 2016 Q4

27. Thank You
27