Neo4j is a graph database platform for connected data. The document introduces Neo4j and discusses how connected data and relationships between data are increasingly important for business value. It provides examples of how Neo4j is used by organizations for applications like fraud detection, personalization, and network analysis. The document also summarizes Neo4j's capabilities like real-time transaction processing, analytics, and visualization and highlights its native graph architecture and performance advantages over traditional databases. Finally, it briefly describes Neo4j's key architecture components and how it can be used for common data architecture patterns.

1. Introducing Neo4j
The Leading Platform for Connected Data

2. Agenda
• About Neo4j
• How to Succeed in the Age of Connected Data
• Connected Data in Supply Chain
• Deep Dive with DZee Solutions

3. Neo4j - The Graph Company
720+
7/10
12/2
5
8/10
53K+
100+
270+
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
• 270+ 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

4. 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

5. Neo4j — Changing the World
ICIJ used Neo4j to uncover the world’s largest
journalistic leak to date, The Panama Papers,
exposing criminals, corruption and extensive
tax evasion.
The US space agency uses Neo4j for their
“Lessons Learned” database to connect
information to improve search ability
effectiveness in space mission.
eBay uses Neo4j to enable machine
learning through knowledge graphs
powering “conversational commerce”.
Knowledge Graph for AIFraud Detection Knowledge Graph for humans

6. 6
• 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 ERP
Real-time promotion
recommendations
Marriott’s Real-time
Pricing Engine
Handling Package
Routing in Real-Time

7. How to Succeed in the
Age of Connected Data

8. 8
Major Forces in a Data-Driven World
2x growth in Data every 3 years
Data Volumes1
People, Processes, Assets,
Devices are Increasingly Related
Rise in Connectedness in Data
2

9. The Rise of Connections in Data
Networks of People
Know
s
Knows
Knows
Knows
Business Processes
Bought
Bought
Viewed
Returned
Bought
Systems & Networks
Tags
Lives_in
Accesse
s
Likes
Works
Devices
E.g., Risk management, Supply
chain, Payments
E.g., Employees, Customers,
Suppliers, Partners,
Influencers
E.g., ID Management, RFID,
Devices & IoT, Supply Chain
Data connections are increasing as rapidly as data volumes

10. 10
Harnessing Connections Drives Business Value
Enhanced Decision
Making
Hyper
Personalization
Massive Data
Integration
Data Driven Discovery
& Innovation
Product Recommendations
Personalized Health Care
Media and Advertising
Fraud Prevention
Network Analysis
Law Enforcement
Drug Discovery
Intelligence and Crime Detection
Product & Process Innovation
360 view of customer
Compliance
Optimize Operations
Connected Data at the Center
AI & Machine
Learning
Price optimization
Product Recommendations
Resource allocation
Digital Transformation Megatrends

11. 10M+
Downloads
3M+ from Neo4j Distribution
7M+ from Docker
Events
400+
Approximate Number of
Neo4j Events per Year
50k+
Meetups
Number of Meetup
Members Globally
Largest pool of graph technologists
50k+
Trained/certified Neo4j
professionals
Trained Developers

12. 12
Network Complexity in Supply Chains

13. •Customer experience & service demands (faster, less breakage, free shipping, transparency)
• Omni-channel- Difficult for revenue forecasting and management
• Labor shortages (drivers) / Sharing economy
• Last mile efficiencies (low cost, high service)
•Technology
• Next wave digital technology hype (IoT, robotics, blockchain, 3D printing) but remain flexible to adapt quickly
• Cyber security
•Transparency and Orchestration of services
• Inventory spread across too many locations
• Visibility into inventory mgmt, no coordination between warehouses, stores and even sales (Data Integration)
• No product traceability especially in medicine and agriculture
•Globalization
• Regulations (Intl, Fed, State, Local)
• Handling goods, data, services
13
2018 SCM challenges

14. Neo4j
The Leading Platform for Connected Data

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

16. Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers & APIs
AI
Neo4j Database 3.3
• 50% faster writes
• Real-time transactions
and traversal applications
The Neo4j Graph Platform surrounds Neo4j 3.3
Neo4j Desktop, the developers’
mission control console
• Free, registered local license
of Enterprise Edition
• APOC library installer
• Algorithm library installer
Data Integration
• Neo4j ETL reveals RDBMS
hidden relationships upon
importing to graph
• Data Importer for fast data
ingestion
• Data Lake integrator materializes
graphs from Apache Hadoop,
Hive and Spark
Graph Analytics
• Graph Algorithms support
PageRank, Centrality and
Path Finding
• Cypher for Apache Spark
from openCypher.org
supports graph composition
(sub-graphs) and algorithm
chaining
Discovery & Visualization
• Integration with popular
visualization vendors
• Neo4j Browser and custom
visualizations allow graph
exploration
Bolt, GraphQL, Java and more
• Secure, Causal Clustering
• High-speed analytic processing
• On-prem, Docker & cloud delivery

17. Connects Roles, Processes & Systems That Surround Data Hub
Data Scientists
Real-time
Graph traversal
Applications
Developers
& Prod Mgrs
Analysts and
Business Users
Big Data IT &
Architecture
ID, Auth & Security
Network & IT Ops
Metadata
Management
360⁰
Marketing
Customer 360
Real-time
Cybersecurity
Chief Officers of …
Compliance, Data, Digital,
Information, Innovation,
Marketing, Operations, Risk &
Security…

18. Neo4j Advantages
18

19. Store / Retrieve
Native Graph Architecture Advantage

20. Load Data
Store / Retrieve
Native Graph Architecture Advantage

21. Load Data
Actionable InsightsStore / Retrieve
Neo4j reveals
connections in your
data
Native Graph Architecture Advantage

22. Index-free adjacency ensures lightning-
fast retrieval of data and relationships
Native Graph Architecture Advantage
Index free adjacency
Unlike other database models Neo4j
connects data as it is stored

23. • Operational workloads
• Analytics workloads
Real-time Transactional
and Analytic Processing • Interactive graph exploration
• Graph representation of data
Discovery and Visualization
• Native property graph model
• Dynamic schema
Agility
• Cypher - Declarative query language
• Procedural language extensions
• Worldwide developer community
Developer Productivity
• 10x less CPU with index-free adjacency
• 10x less hardware than other platforms
Hardware efficiency
Neo4j: Graph Platform Benefits
Performance
• Index-free adjacency
• Millions of hops per
second

24. 1
2
3
4
5
6
Key Architecture Components
Index-Free Adjacency
In memory and on flash/disk
vs
ACID Foundation
Required for safe writes
Full-Stack Clustering
Causal consistency
Language, Drivers, Tooling
Developer Experience,
Graph Efficiency, Type Safety
Graph Engine
Cost-Based Optimizer, Graph
Statistics, Cypher Runtime
Hardware Optimizations
For next-gen infrastructure

25. 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

26. How Neo4j Differentiates from other Databases
Visualization
Queries
Processing
Storage
Non-Native Graph DBNative Graph DB
RDBM
S
Optimized for graph workloads

27. Case Studies
Some examples from our customers

28. Real World Implementation
A Connections First Approach to Supply Chain
Management
Ashwin Pingali
CTO, Apps Consultants Inc.