The document discusses Neo4j, a graph database platform, including its adoption rates, use cases, and new features in version 3.2 like improved performance, global clustering capabilities, and security features. It also explores how graph databases and knowledge graphs are important for machine learning and how eBay uses Neo4j to power recommendations.

2. Emil Eifrem
CEO & Co-Founder Neo4j

3. Welcome!
#neo4j#graphconnect

5. ACCOUNT
ADDRESS
PERSON
PERSON
NAME
STREET
BANK
NAME
COMPANY
BANK
BAHAMAS

6. Person
B
Bank US
Account
Person
A
Compan
y
Bank
Bahama
s
AddressNODE
RELATIONSHIP

11. ICIJ Pulitzer Price Winner 2017

12. Neo4j Connected Data Fellowship Award
www.neo4j.com/datafellowship

13. Finding a Cure for Cancer

17. PHARMA DB GENOMIC DATA PATIENT
RECORDS
TRIAL DATA DRUGS DB LAB DATA
Data Stored in Disparate Silos

18. Johnson Space Center
Houston, Texas

22. “Lessons Learned Database”
A half-century of collective NASA engineering knowledge

23. “Lessons Learned”
Database
GRAPH DB
Load Data

24. “Lessons Learned”
Database
GRAPH DB
Load Data

25. Let’s Hear a Few Stories

26. Let’s Hear a Few Stories
— David Meza, Chief Knowledge Architect at NASA
“Neo4j saved well over two
years of work and one million
dollars of taxpayer funds.”
Impact

28. Neo4j Adoption

29. “Forrester estimates that over
25% of enterprises will be using
graph databases by 2017.”
Forrester Research, 2014

30. Adoption Highlights
Retail
7 out of top 10
retailers in the world
Finance
12 out of 25 top
financial services firms
8 out of top 10
software vendors
Software
(As per 2017)

31. Real-Time
Recommendation
s
Fraud
Detection
Network &
IT
Operations
Master Data
Management
Graph-Based
Search
Identity & Access
Management
Common Graph DB Use Cases

32. Startup Adoption
≤ 20 employees
Free Neo4j Enterprise Subscription
(Unsupported)
≤ 50 employees
Startup Pricing
(Includes Support)
Tiers, Neo4j Startup Program

35. Sustainable Competitive Advantage

36. Case Study: The Consumer Web

37. Connections in Data
Ability to Leverage Connections

38. Connections in Data Ability to Leverage Connections
Function of Time Choice of Technology

39. Good for discrete problems
Insufficient for connected
problems
RDBMS

40. Data lake
Good for Analytics, BI, Map Reduce
Non-Operational, Slow Queries
RDBMS

41. of the Global 2000 are
Using or Piloting Neo4j!
As of today

42. Philip Rathle
VP of Product, Neo4j

43. openCypher

44. Graph Query Language

45. Discrete Data
Problems
Connected Data
Problems
Perspective
SELECT foo
FROM emp
SQL
(Ann)-[:LOVES]->(Dan)
CypherQuery
Language
RDBMS GRAPH DB
DBMS
Architecture

46. Cypher

47. Users Cypher

48. Most Used

49. Sep 2015May 2015Jan 2015Sep 2014May 2014Jan 2014Sep 2013May 2013
100
Popularitychanges
500
600
700
200
300
400
Jan 2013
© DB-Engines.com 2015
• Wide column stores
• RDF stores
• Document stores
• Search engines
• Native XML DBMS
• Key-value stores
• Object oriented DBMS
• Multivalue DBMS
• Times Series DBMS
Relational database
Graph Database
Launch of Cypher

50. Open Source
(Available to anyone)
Apache 2.0
Opening the Language
Open Source
(As part of Neo4j)
GPL v3
Open Process
(Open to anyone)
CIR, CIP, oCIM
Formal Standard
(Standards Body)
e.g. ANSI, ISO

51. Documentation, TCK, Grammar, Parser
openCypher Resources

52. Databases
Tools
ruruki

53. Cypher is Evolving

54. Graph Composition
Cypher
Query
Return
SQL Integration
SQL Cypher
Next Steps for Cypher

55. Evolving the Language Together
Feb ’17, May ’17, TBD
oCIM Summer of Syntax
Twice-Monthly Calls
Cypher Language Group
Github
Cypher Improvement
Requests & Proposals

56. What’s New in Product?

57. Neo4j 3.1
The Graph Foundation for the
Connected Enterprise
December 2016

58. Neo4j 3.2
The Graph Foundation for Global
Internet Scale Applications

59. I
Global Scale
Introducing Neo4j 3.2
Built for global internet
applications
Native Perfomance
III
Continuous improvements
in graph performance
II
Governance & Security
Enterprise governance for
the connected enterprise

60. Global Scale
Built for global internet
applications

61. Neo4j Enterprise 3.1
Causal Clustering
Ultra-High
Throughput
Guaranteed
Redundancy
Read-your-own-
Writes
Built-in Routing

62. Global Cluster
Topologies
Geo Aware
Load Balancing
Tiered Replicas
Full-Stack API
US EAST GROUP
UK GROUP
HK GROUP
SA GROUP
Now in Neo4j 3.2: Multi-DC Clustering

63. I
Global Scale
Introducing Neo4j 3.2
Built for global internet
applications
Native Perfomance
III
Continuous improvements
in graph performance
II
Governance & Security
Enterprise governance for
the connected enterprise

64. Governance & Security
Enterprise governance for
the connected enterprise

65. Governance & Security Foundation
LDAP & Active
Directory
User & Roles Procedure Access
Controls

66. Kerberos
Strong Security
Governance & Security Foundation
Coming Soon!
Intra-Cluster Encryption
Available in Neo4j 3.2
*businessUnit
*customerID
infoProperties
Node Keys
Schema Constraints

67. I
Global Scale
Introducing Neo4j 3.2
Built for global internet
applications
Native Perfomance
III
Continuous improvements
in graph performance
II
Governance & Security
Enterprise governance for
the connected enterprise

68. Native Label Index: Writes now 30-300% faster
Composite Indexes : Exact lookups for multiple properties
Reachability Queries: Can improve by orders of magnitude
Compiled Cypher Runtime: Speeds queries up to 300%
Neo4j Browser: Ground-up rewrite yields snappier performance
Native Graph Performance
Improvements in Neo4j 3.2

69. One more thing…

70. Neo4j 3.2
Available Now
Visit neo4j.com/download

71. Emil Eifrem
CEO & Co-Founder Neo4j

72. Machine Learning
Deep Learning

73. Machine Learning is Based on Graphs

74. Machine Learning is Based on Graphs

75. Knowledge Graphs

76. Context drives meaning and
precision for Machine
Learning systems

77. FATHER_OF DRIVE

78. Knowledge Graphs
reminders in Inbox smart messaging
in Allo
Google Photos

79. Knowledge Graphs with Neo4j

80. Case Study: Knowledge Graphs at eBay

81. Case Study: Knowledge Graphs at eBay

82. Case Study: Knowledge Graphs at eBay

83. Case Study: Knowledge Graphs at eBay

84. Case Study: Knowledge Graphs at eBay
Bags

85. Men’s Backpack
Handbag
Case Study: Knowledge Graphs at eBay

86. Case Study: Knowledge Graphs at eBay
https://shopbot.ebay.com/
Try it out at:

87. A Highly Connected Future

89. Your Homework - Connect