1) Neo4j is a native graph database platform that allows users to store, reveal, and query data relationships in real-time. It is designed specifically for graph databases.
2) Graph databases represent data as nodes and relationships, which provides a more connected view of data compared to relational databases. This connected view of data drives insights and applications in areas like recommendations, fraud detection, and knowledge graphs.
3) Neo4j has over 250 enterprise customers across industries like retail, financial services, and telecom. It is widely used for applications like recommendations, fraud detection, network analysis, and knowledge graphs.
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Neo4j GraphTalk Florence - Introduction to the Neo4j Graph Platform
1. Welcome to GraphTalk Florence
Neo4j – The Graph Platform
Bill Brooks
Territory Manager, South Europe
Neo4j
bill@neo4j.com
2. Connectedness Represented in Graphs
C
C
A AA
U
S S SS S
USER_ACCESS
CONTROLLED_BY
SUBSCRIBED _BY
User
Customers
Accounts
Subscriptions
VP
Staff Staff StaffStaff
DirectorStaffDirector
Manager Manager Manager Manager
Fiber
Link
Fiber
Link
Fiber
Link
Ocean
Cable
Switch Switch
Router Router
Service
Organizational
Hierarchy
Product
Subscriptions
Network
Operations
Social
Networks
5. Graph Transformation Maturity
Context Paths
Auto-Graphs
Graph Layers
1st Graph
Cross-Connect
Cross-tech applications
Internet of Things
operations
Transparent Neural
Networks
Blockchain-managed
systems
Adjacent graph layers
inspire new innovations
Metadata / Risk
Management
Knowledge Graphs
AI- Powered Customer
Experiences
Connect unlike objects
such as people to products,
locations
Mobile app explosion
Recommendation engines
Fraud detectors
Desire for more context to
follow connections
Connects like objects
People, computer
networks, telco, etc
6. Density Drives Value In Graphs
Metcalfe’s Law of the Network (V=n2)
5 hops < less Value
100’s of hops deliver
immense VALUE
7. Neo4j Solves Connected, Real-Time Problems
Connectedness
Batch-Precompute Real-Time
Data Information Knowledge Insight Wisdom
Latency & Freshness
8. 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
9. Who We Are: Neo4j - The Graph Platform
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
• Performance
• ACID Transactions
• Agility
• Graph Algorithms
Designed, built and tested natively
for graphs from the start for:
• Developer Productivity
• Hardware Efficiency
• Global Scale
• Graph Adoption
10. 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
Neo4j - The Graph Company
Ecosystem
Startups in program
Enterprise customers
Partners
Meet up members
Events per year
Industry’s Largest Dedicated Investment in Graphs
13. 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
14. 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
15. "Neo4j continues to dominate
the graph database market.”
October, 2017
“Customers choose Neo4j
to drive innovation.”
February, 2018
“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. 2010 2011 2012 2013 2015 2017
Frustrated with
Gremlin, Neo
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.org
open sourced
Cypher query
language as de
facto standard
Industry’s
1st Graph
Platform
Graph Algorithms
for data scientists
Developer’s Neo4j
Desktop
2014
Visual Graph
Query Browser
2016
Causal
Consistency
for Graphs
Neo4j—The Graph Innovator
2018 2019
Morpheus
Graph is a
unique
paradigm
Neo4j Cloud
Neo4j Cloud EAP
Neo4j Bloom visual discovery
Cypher for Apache Spark
Cypher for Gremlin
GQL Manifesto
17. CAR
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
PERSON PERSON
18. Cypher: Powerful and Expressive Query Language
MATCH (:Person { name:“Dan”} ) -[:MARRIED_TO]-> (spouse)
MARRIED_TO
Dan Ann
NODE RELATIONSHIP TYPE
LABEL PROPERTY VARIABLE
19. Why Cypher is Better
Ease of use drives adoption & popularity
• Demonstrable maturity and proven success
• Huge ecosystem and support network
• Visibly represents relationships & paths
• Declarative language is easy to learn
Cypher is Open, Easy and Everywhere
Cypher on Apache
Spark (CAPS)
Cypher ToolingBI Tools
Integration
Tools Cypher on …
Additional Sources
Apache Hadoop
Accelerating Market Adoption
• openCypher participation is growing
• Reference model for ISO, other research projects
• SQL compatible and complementary
• Released for under friendly Apache license
Evolving and Expanding Rapidly
Incorporating new ideas for Cypher such as:
• Return results as graphs OR tables of data (composability)
• compose subqueries and chain-linking query algorithms
• build graph expressions
• define new graph object types like walks, runs and paths
20. Graph Platform: Connects to Many Roles in Enterprise
DEVELOPERS
ADMINS
Graph
Analytics
Graph
Transactions
DATA
ANALYSTS
DATA
SCIENTISTS
APPLICATIONS
Drivers & APIs
Data Integration
BIG DATA IT
Analytics
Tooling
BUSINESS USERS
Discovery & Visualization
Development &
Administration
22. Neo4j Graph Algorithms
Finds the shortest path or
evaluates route
availability and quality
Evaluates how a
group is clustered or
partitioned
Determines the
importance of distinct
nodes in the network
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. Connecting Roles & Projects around Enterprise Data Hub
Data Scientists
Real-time
Graph traversal
Applications
Developers
& Prod Mgrs
Analysts and
Business Users
Chief Officers of …
Compliance, Data, Digital,
Information, Innovation,
Marketing, Operations, Risk &
Security…
Big Data IT &
Architecture
ID, Auth & Security
Network & IT Ops
Metadata
Management
360⁰
Marketing
Customer 360
Real-time
Cybersecurity
Account navigation
• Multiple paths through
organization
• Graphs have strong
appetite for data to add
nodes & increase density
of relationships
• Value of graph increase
according to Metcalfe’s
Law (V=n2)
• Customer applications
iterate every 3 months
26. 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
27. Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers & APIs
AI
Neo4j Database 3.4
• 70% faster Cypher
• Native String Indexes
(up to 5x faster writes)
• 100B+ bulk importer
Improved Admin Experience
• Rolling upgrades
• 2x faster backups
• Cache Warming on startup
• Improved diagnostics
Morpheus for Apache Spark
• Graph analytics in the data lake
• In-memory Spark graphs from
Apache Hadoop, Hive, Gremlin
and Spark
• Save graphs into Neo4j
• High-speed data exchange
between Neo4j & data lake
• Progressive analysis using named
graphs
Graph Data Science
• High speed graph algorithms
Neo4j Bloom
• New graph illustration and
communication tool for non-
technical users
• Explore and edit graph
• Search-based
• Create storyboards
• Foundation for graph data
discovery
• Integrated with graph platform
Multi-Cluster routing built into Bolt drivers
• Date/Time data type
• 3-D Geospatial search
• Secure, Horizontal Multi-Clustering
• Property-value Security
The Neo4j Graph Platform, Summer 2018
28. Neo4j Bloom Features
28
• Prompted Search
• Property Browser &
editor
• Category icons and
color scheme
• Pan, Zoom & Select
29. Different Data Types Morph
Tables into Graphs, Graphs into Tables
Morpheus for Apache Spark:
Future:
Any Kettle Source
RDBMS & JSON
Future:
Other Graph Data Sources