This document provides an introduction to graph databases and their advantages over relational and NoSQL databases for modeling connected data. It discusses how graph databases can unlock value from data relationships in areas like recommendations, fraud detection, and identity management. The document explains that graph databases allow flexible modeling of nodes and relationships, powerful graph queries, and the ability to easily add new types of data over time. It presents the example of Neo4j as the leading graph database and discusses how early adopters were able to gain competitive advantages through new applications and insights leveraging their connected data in a graph model.

1. Graph All The Things!
Introduction to Graph Database

2. What do these companies have in common?

3. Realizing Value from Data Relationships in Consumer Web

4. Realizing Value from Data Relationships in Consumer Web

5. Realizing Value from Data Relationships in Consumer Web

6. Ref: http://www.gartner.com/id=2081316
Interest Graph
Payment Graph
Intent Graph
Mobile Graph
Social Graph
Gartner: Competitive Dynamics of Consumer Web
Five Graphs Deliver a Sustainable Advantage

7. High Business Value in Data Relationships
Data is increasing in volume…
• New digital processes
• More online transactions
• New social networks
• More devices
Using Data Relationships unlocks value
• Real-time recommendations
• Fraud detection
• Master data management
• Network and IT operations
• Identity and access management
• Graph-based search… and is getting more connected
Customers, products, processes,
devices interact and relate to
each other
Early adopters became industry leaders

8. Unlocking Value from Your Data Relationships
1. Model your data as a graph of data
and relationships
2. Use relationship information in
real-time to transform your
business
3. Add new relationships on the fly to
adapt to your changing business

9. Relational DBs Can’t Handle Data Relationships Well
• Cannot model or store data and relationships
without complexity
• Performance degrades with number and levels
of relationships, and database size
• Query complexity grows with need for JOINs
• Adding new types of data and relationships
requires schema redesign, increasing time to
market
… making traditional databases inappropriate
when data relationships are valuable in real-time
Slow development
Poor performance
Low scalability
Hard to maintain

10. NoSQL Databases Don’t Handle Data Relationships
• No data structures to model or store
relationships
• No query constructs to support data
relationships
• Relating data requires “JOIN logic”
in the application
• No ACID support for transactions
… making NoSQL databases inappropriate when
data relationships are valuable in real-time

11. Graph Databases – Re-Imagine Your Data as a Graph
An enterprise-grade graph database
enables you to:
• Model and store your data as a graph
• Query data relationships with ease
and in real-time
• Seamlessly evolve applications to
support new requirements by
adding new kinds of data and
relationships
Agile development
High performance
Vertical and horizontal scale
Seamless evolution

12. “Forrester estimates that over 25% of enterprises will be using
graph databases by 2017”
The Graph Database Revolution
“Graph analysis is possibly the single most effective competitive
differentiator for organizations pursuing data-driven operations
and decisions after the design of data capture.”
“Neo4j is the current market leader in graph databases.”
IT Market Clock for Database Management Systems, 2014
https://www.gartner.com/doc/2852717/it-market-clock-database-management
TechRadar™: Enterprise DBMS, Q1 2014
http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801
Graph Databases – and Their Potential to Transform How We Capture Interdependencies (Enterprise Management Associates)
http://blogs.enterprisemanagement.com/dennisdrogseth/2013/11/06/graph-databasesand-potential-transform-capture-interdependencies/

13. Graph Databases – The Fastest Growing DBMS Category
Source: http://db-engines.com/en/ranking/graph+dbms
500% increase in popularity over the last 2 years:

14. Graph Database Fundamentals

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

16. The Whiteboard Model Is the Physical Model

17. CAR
name: “Dan”
born: May 29, 1970
twitter: “@dan”
name: “Ann”
born: Dec 5, 1975
since:
Jan 10, 2011
brand: “Volvo”
model: “V70”
Property Graph Model Components
Nodes
• The objects in the graph
• Can have name-value properties
• Can be labeled
LOVES
LOVES
LIVES WITH
PERSON PERSONRelationships
• Relate nodes by type and direction
• Can have name-value properties

18. Relational Versus Graph Models
Relational Model Graph Model
KNOWS
ANDREAS
TOBIAS
MICA
DELIA
Person FriendPerson-Friend
ANDREAS
DELIA
TOBIAS
MICA

19. Graph Query Language: Cypher
MATCH (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} )
LOVES
Dan Ann
NODE NODE
LABEL PROPERTYLABEL PROPERTY

20. MATCH (boss)-[:MANAGES*0..3]->(sub),
(sub)-[:MANAGES*1..3]->(report)
WHERE boss.name = “John Doe”
RETURN sub.name AS Subordinate,
count(report) AS Total
Express Complex Relationship Queries Easily
Find all direct reports and how
many people they manage,
up to 3 levels down
Cypher Query
SQL Query

21. Real-Time Query Performance
Graph Versus Relational and Other NoSQL Databases
Connectedness and Size of Data Set
ResponseTime
0 to 2 hops
0 to 3 degrees
Thousands of connections
Tens to hundreds of hops
Thousands of degrees
Billions of connections
Relational and
Other NoSQL
Databases
Neo4j
Neo4j is
1000x faster
“Minutes to
milliseconds”

22. Building Competitive Advantage
Using Graphs

23. Value from Data Relationships
Common Use Cases
Internal Applications
Master Data Management
Network and
IT Operations
Fraud Detection
Customer-Facing Applications
Real-Time Recommendations
Graph-Based Search
Identity and
Access Management

24. Customers Achieve Sustainable Competitive Advantage
By Adopting Neo4j
New Products & Services Leveraging Data
Relationships
• First to market, up and running in days, not
weeks or months
• Reduced churn, increasing engagement and
uncovering fraud
• Achieved new company vision centered
around Business Graph
• Leapfrogged the competition with a 360
degree view of the customer
Reimagine Existing Applications, and Innovate with Data
Relationships
• Kept the business running when data growth threatened
to stop it
• Drastically reduced project complexity and risk
• Increased revenue and delighted customers by improving
user experience
• Brought new offering to market to compete with Amazon
Prime & Fresh, and Google Express

25. Bringing a Graph Database in
your Environment

26. Data Storage and
Business Rules Execution
Data Mining
and Aggregation
Graph Database Fits into Your Enterprise Environment
Application
Graph Database Cluster
Neo4j Neo4j Neo4j
Ad Hoc
Analysis
Bulk Analytic
Infrastructure
Hadoop, EDW …
Data
Scientist
End User
Databases
Relational
NoSQL
Hadoop

27. MIGRATE
ALL DATA
MIGRATE
GRAPH DATA
DUPLICATE
GRAPH DATA
Non-graph data Graph data
Graph dataAll data
All data
Relational
Database
Graph
Database
Application
Application
Application
Options for Maintaining Your Data in the Graph

28. Quick Start: Plan Your Project
1
2
3
4
5
6
7
8
Learn Neo4j
Decide on Architecture
Import and Model Data
Build Application
Test Application
All projects vary, but
timelines as short as 8
weeks are not unusual
PROFESSIONAL SERVICES PLAN

29. (Market) - [:LOVES] - > (Graphs)

30. Users Love Neo4j

31. Users Love Neo4j
“We found Neo4j to be
literally thousands of times
faster than our prior MySQL
solution, with queries that
require 10 to 100 times less
code. Today, Neo4j provides
eBay with functionality that
was previously impossible.”
Volker Pacher
Senior Developer
Horizontal Scaling
“The ability to have flexible schema and horizontal
scalability is key to our success with Neo4j.”
- IT Director, G5000 Professional Services Firm
Social Recommendations
“Neo4j has allowed us to integrate personalized user
experiences—based on our users’ social relationships—
into both product and marketing.”
- Craig Follett, CEO, Universe
True Game Changer
“Things that were impossible became possible.”
- Markus Paaso, Developer, Sagire Software

32. There Are Lots of Ways to Easily Learn

33. Thanks!
Q&A