Neo4j GraphTalk Wien Dirk Möller, Neo4j

1. Graph Talk Wien
#1 Database for Connected Data
Dirk Möller
Director Sales CEMEA
dirk@neo4j.com
18/9/19

2. Neo4j GraphTalks
Network & Application Management
• Einführung in Graphdatenbanken und Neo4j (9.30-10.00)
Bruno Ungermann
• Neue Herangehensweisen für Network und Application Mgt mit Graphen (10.00-11.00)
Stefan Kolmar
• Wie werden Graphdatenbank-Projekte mit Neo4j zum Erfolg? (11.00-11.30)
Stefan Kolmar
• Q&A

3. Agenda!
• Impact of Graphs
• State of the Graph
• Three waves
• What‘s enabling all of this?
• Use Cases

5. ACCOUNT
HAS
REGISTERED
ADDRESS
PERSON
IS_OFFICER_OF
PERSON
NAME
STREET
BANK
WITH
NAME
COMPANY
BANK
BAHAMAS
2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc…

6. 2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc… Person
B
Bank US
Account
123
Person
A
Acme
Inc
Bank
Bahama
s
Address
X
HAS_ACCOUNT
REGISTERED
IS_OFFICER_OF
WITH
NODE
RELATIONSHIP

7. 2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc…

11. ICIJ Pulitzer Price Winner 2017

15. State of the graph

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

17. Popularity of Graphs
DB-engines Ranking of Database Categories
• Graph DBMS
• Key-value stores
• Document stores
• Wide column store
• RDF stores
• Time stores
• Native XML DBMS
• Object oriented DBMS
• Multivalue DBMS
• Relational DBMS
Graph DB
2013 2014 2015 2016 2017 2018

18. Software
Financial
Services
Telecom
Retail &
Consumer Goods
Media &
Entertainment
Other Industries
Airbus
Over 300 Enterprises and 10s of
Thousands of Projects on Neo4j

19. 7 of the Top 10 Software
Companies Use Neo4j

20. 8 of the Top 10 Insurance
Companies Use Neo4j

21. Category Defining Use Cases
airbnb
Fraud
Detection
Real-Time
Recommendations
Network & IT
Operations
Master Data
Management
Knowledge
Graph
Identity & Access
Management

22. 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

23. 2012 à 2018
May 10th-11th, London
CONFERENCE
+
TRAINING

24. 700+

25. >50%of enterprises are using
graph databases
As of today
Source: Forrester Vendor Landscape: !
Graph Databases, October 6, 2017!

26. "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!

28. Three waves

29. Our core belief is — connections between data
are as important as the data itself

30. Reveal connections? Look at this data

31. Look at the same data as a graph

33. Graph Based Success

35. Retail
7 of top 10
Finance
20 of top 25
7 of top 10
Software
Hospitality
3 of top 5
Telco
4 of top 5
Airlines
3 of top 5
Logistics
3 of top 5
76%
FORTUNE 100
have adopted or
piloted Neo4j

36. Real-Time
Recommendations
Dynamic Pricing
Artificial Intelligence
& IoT-applications
Fraud Detection
Network
Management
Customer
Engagement
Supply Chain
Efficiency
Identity and Access
Management
Relationship-Driven Applications!

37. 37
• 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

38. Home
Security
Internet
of things
Institutional
Memory
Entertainment
Recommendations
Home
Operations
Personalization
Voice Enabled Smart Home

39. More Data Enables
More Use Cases

40. Data Network Effect
“A product, generally powered by machine learning, becomes smarter
as it gets more data from your users. The more users use your product,
the more data they contribute; the more data they contribute, the
smarter your product becomes.”
— Matt Turck

41. What’s Enabling All of This?

42. A year ago…

43. 43!
Neo4j Graph Platform!
Development &
Administration
Analytics
Tooling
BUSINESS USERS
DEVELOPERS
ADMINS
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & Visualization
DATA
ANALYSTS
DATA
SCIENTISTS
Drivers & APIs
APPLICATIONS
AI

44. Neo4j Bloom

46. Case Studies
Some examples from our customers

47. REAL-TIME RECOMMENDATIONS
ML-BASED COMMERCE
TRACKING MULTI-DIMENSIONAL
SOCIAL ACTIVITY
TRANSFORMING
CUSTOMER SELF-SERVICE
PERSONALIZATION ENGINES
Over 200 Customers, Including some of
the World’s Largest Companies

49. Case Study: Knowledge Graphs at eBay

50. Case Study: Knowledge Graphs at eBay

51. Case Study: Knowledge Graphs at eBay

52. Case Study: Knowledge Graphs at eBay
Bags

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

54. Case study
Solving real-time recommendations for the
World’s largest retailer.
Challenge
• In its drive to provide the best web experience for its
customers, Walmart wanted to optimize its online
recommendations.
• Walmart recognized the challenge it faced in delivering
recommendations with traditional relational database
technology.
• Walmart uses Neo4j to quickly query customers’ past
purchases, as well as instantly capture any new interests
shown in the customers’ current online visit – essential
for making real-time recommendations.
Use of Neo4j
“As the current market leader in
graph databases, and with
enterprise features for scalability
and availability, Neo4j is the right
choice to meet our demands”.
- Marcos Vada, Walmart
• With Neo4j, Walmart could substitute a heavy batch
process with a simple and real-time graph database.
Result/Outcome

55. Case study
eBay Now Tackles eCommerce Delivery Service Routing with
Neo4j
Challenge
• The queries used to select the best courier for eBays
routing system were simply taking too long and they
needed a solution to maintain a competitive service.
• The MySQL joins being used created a code base too slow
and complex to maintain.
• eBay is now using Neo4j’s graph database platform to
redefine e-commerce, by making delivery of online and
mobile orders quick and convenient.
Use of Neo4j
• With Neo4j eBay managed to eliminate the biggest
roadblock between retailers and online shoppers: the
option to have your item delivered the same day.
• The schema-flexible nature of the database allowed easy
extensibility, speeding up development.
• Neo4j solution was more than 1000x faster than the prior
MySQL Soltution.
Our Neo4j solution is literally
thousands of times faster than the
prior MySQL solution, with queries
that require 10-100 times less code.
Result/Outcome
– Volker Pacher, eBay

56. Top Tier US
Retailer
Case study
Solving Real-time promotions for a top US
retailer
Challenge
• Suffered significant revenues loss, due to legacy
infrastructure.
• Particularly challenging when handling transaction volumes
on peak shopping occasions such as Thanksgiving and Cyber
Monday.
• Neo4j is used to revolutionize and reinvent its real-time
promotions engine.
• On an average Neo4j processes 90% of this retailer’s 35M+
daily transactions, each 3-22 hops, in 4ms or less.
Use of Neo4j
• Reached an all time high in online revenues, due to the
Neo4j-based friction free solution.
• Neo4j also enabled the company to be one of the first
retailers to provide the same promotions across both online
and traditional retail channels.
“On an average Neo4j processes
90% of this retailer’s 35M+ daily
transactions, each 3-22 hops, in
4ms or less.”
– Top Tier US Retailer
Result/Outcome

57. 57
https://www.slideshare.net/neo4j/volvo-cars-build-a-car-with-neo4j

58. 58
https://www.slideshare.net/neo4j/generali-fraud-analytics

59. 59
https://www.slideshare.net/neo4j/daimler-ag-structurecube-die-gklasse-im-sumpf-der-strukturen

60. 60
https://www.slideshare.net/neo4j/graphtour-madrid-running-neo4j-on-a-large-scale-image-platform

61. Use cases on https://neo4j.com/use-cases/

62. A Highly Connected Future

64. Your Homework - Connect