Bruno Ungermann Neo4j GraphTalk Frankfurt

1. Herzlich Willkommen!
1
bruno.ungermann@neo4j.com

2. Neo4j GraphTalks
DSGVO & Compliance
• Einführung in Graphdatenbanken und Neo4j (9.30-10.00)
Bruno Ungermann
• Strategische Vorteile von DSGVO durch Nutzen von verbundenen Daten (10.00-11.00)
Stefan Kolmar
• Wie werden Graphdatenbank-Projekte mit Neo4j zum Erfolg? (11.00-11.30)
Stefan Kolmar
• Q&A

3. Complexity

4. The Internet (of Things)

5. Domain Model Logistics Process

6. Traditional Approach: Fixed Schema, Tables

7. Graph Model: Nodes & Relationships
Container
Load
USING ROUTE
Depart 2014-04-15
Arrive 2014-04-28
USING_CARRIER
Vessel
Physical
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Shipment Carrier
Emission
Class A
Shipment:
ID 256787
Carrier:
DHL
Route
10520km
Route:
823km
Fueling
Max Wgt
80
Type Gas
B
Town:
Tokyo
Town:
Hong
Kong
Town:
Hamburg
Container
LoadContainer
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Weight
15.5kg
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8. Intuitiveness

9. Flexibility

10. Flexibility & Agility

11. “We found Neo4j to be literally thousands of times
faster than our prior MySQL solution, with queries
that require 10-100 times less code. Today, Neo4j
provides eBay with functionality that was previously
impossible.” - Volker Pacher, Senior Developer
“Minutes to milliseconds” performance
Queries up to 1000x faster than other tested database types
Speed

12. Neo4j - The Graph Company
500+
7/10
12/25
8/10
53K+
100+
250+
450+
Adoption
Top Retail Firms
Top Financial Firms
Top Software Vendors
Customers Partners
• Creator of the Neo4j Graph Platform
• ~200 employees
• HQ in Silicon Valley, other offices include
London, Munich, Paris and Malmö
(Sweden)
• $80M in funding from Fidelity, Sunstone,
Conor, Creandum, and Greenbridge
Capital
• Over 10M+ downloads,
• 250+ 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

13. 2010 2011 2012 2013 2015 2017
Invented Cypher -
Leading language
for graph queries
First open source GA
version of a property
graph database
O’Reilly Graph
Database —
first definitive
book for graph
professionals
Introduced
labels to
simplify graph
modeling
openCypher Project
— open sourced
Cypher to create the
de facto standard
Launched
industry’s
first Graph
Platform
Neo4j — The Graph Technology Pioneer
2014
Visual Graph
Query Browser
2016
Causal
Consistency
for Graphs

14. 2012  2018
May 10th-11th, London
CONFERENCE
+
TRAINING

15. "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
DBMSA
“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
Graph is a Unique Paradigm

16. Graph Based Success

17. 17
• 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

18. Discrete Data
Minimally
connected data
Neo4j is designed for data relationships
Other NoSQL
Relational
DBMS
Neo4j Graph DB
Connected Data
Focused on
Data Relationships
Development Benefits
Easy model maintenance
Easy query
Deployment Benefits
Ultra high performance
Minimal resource usage
Use the Right Database for the Right Job

19. Graph
Transactions
Graph
Analytics
Data Integration
Development
& Admin
Analytics
Tooling
Drivers & APIs Discovery & Visualization
Developers
Admins
Applications Business Users
Data Analysts
Data Scientists

20. Neo4j Bloom Features
20
• Prompted Search
• Property Browser &
editor
• Category icons and
color scheme
• Pan, Zoom & Select

21. 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

22. 22
Real-Time
Recommendations
Fraud
Detection
Network &
IT Operations
Master Data
Management
Knowledge
Graph
Identity & Access
Management
Common Graph Technology Use Cases
AirBnb

23. Background
• Panama based lawyers Mossack & Fonseca do
business in hosting “letterbox companies”
• Suspected to support tax saving and organized
crime
• Altogether: 2.6 TB, 11 milo files, 214.000 letter
box companies
Business Problem
• Goal to unravel chains Bank-Person–Client–
Address–Intermediaries – M&F
• Earlier cases: spreadsheet based analysis (back-
and-forth) & pencil to extract such connections
• This case: sheer amount of data & arbitrarily chain
length condemn such approaches to fail
Solution and Benefits
• 400 journalists, investigate/update/share, 2 people
with IT background
• Identify connections quickly and easily
• Fast Results wouldn‘t be possible without GraphDB
Panama/Paradise Papers
Fraud Detection23

25. Herausforderungen DSGVO

26. Nachverfolgung personenbezogener Daten

27. Vorteile Graphtechnologie für DSGVO

28. In vier Schritten zur DSGVO-Compliance

29. How to Start

30. Whiteboard Session

31. Bootcamp