Learn how to enhance your application by using Neo4j and MongoDB together. Polyglot persistence is the concept of taking advantage of the strengths of different database technologies to improve functionality and enhance your application. In this webinar we will examine some use cases where it makes sense to use a document database (MongoDB) with a graph database (Neo4j) in a single application. Specifically, we will show how MongoDB can be used to provide search and browsing functionality for a product catalog while using Neo4j to provide personalized product recommendations. Finally we will look at the Neo4j Doc Manager project which facilitates syncing data from MongoDB to Neo4j to make polyglot persistence with MongoDB and Neo4j much easier.

1. NoSQL Polyglot Persistence
Using Neo4j and MongoDB together
William Lyon
@lyonwj

2. William Lyon
Developer Relations Engineer @neo4j
will@neo4j.com
@lyonwj
lyonwj.com

3. Does Neo4j work with ______ ?
Languages, frameworks, databases…

4. Does Neo4j work with ______ ?
Languages

5. Does Neo4j work with ______ ?
Frameworks

6. Does Neo4j work with ______ ?
Frameworks

7. Does Neo4j work with ______ ?
Deployment

8. Does Neo4j work with ______ ?
Databases

9. Does Neo4j work with ______ ?
Languages, frameworks, databases…

10. Does Neo4j work with ?

11. Why?
+

12. MongoDB
Features
• NoSQL database
• Document datamodel
• JSON-like documents (BSON)
• Flexible data model
• Horizontal scalability (sharding)
• Complex queries
{
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"keynote",
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"room": "Auditorium",
"timeslot": "Wed 29th, 09:30-10:30",
"speaker": {
"name": "Juergen Hoeller",
"bio": "Juergen Hoeller is co-founder of the Spring Framework open source
project.",
"twitter": "https://twitter.com/springjuergen",
"picture": "http://www.springio.net/wp-content/uploads/2014/11/
juergen_hoeller-220x220.jpeg"
}
}

13. MongoDB
Use Cases
• Product catalog
• User profiles
• Metadata
• Content
• Events
• Analytics
{
"session": {
"title": "12 Years of Spring: An Open Source Journey",
"abstract": "Spring emerged as a core open source project in early 2003 and
evolved to a broad portfolio of open source projects up until 2015."
},
"topics": [
"keynote",
"spring"
],
"room": "Auditorium",
"timeslot": "Wed 29th, 09:30-10:30",
"speaker": {
"name": "Juergen Hoeller",
"bio": "Juergen Hoeller is co-founder of the Spring Framework open source
project.",
"twitter": "https://twitter.com/springjuergen",
"picture": "http://www.springio.net/wp-content/uploads/2014/11/
juergen_hoeller-220x220.jpeg"
}
}
https://www.mongodb.com/use-cases/

14. MongoDB
Use Cases
• Product catalog
• User profiles
• Metadata
• Content
• Events
• Analytics
{
"session": {
"title": "12 Years of Spring: An Open Source Journey",
"abstract": "Spring emerged as a core open source project in early 2003 and
evolved to a broad portfolio of open source projects up until 2015."
},
"topics": [
"keynote",
"spring"
],
"room": "Auditorium",
"timeslot": "Wed 29th, 09:30-10:30",
"speaker": {
"name": "Juergen Hoeller",
"bio": "Juergen Hoeller is co-founder of the Spring Framework open source
project.",
"twitter": "https://twitter.com/springjuergen",
"picture": "http://www.springio.net/wp-content/uploads/2014/11/
juergen_hoeller-220x220.jpeg"
}
}
https://www.mongodb.com/use-cases/

15. Neo4j
Graph Database
• Property graph data model
• Nodes and relationships
• Native graph processing
• Cypher query language

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

17. Cypher: SQL for graphs
CREATE (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} )
LOVES
Dan Ann
LABEL PROPERTY
NODE NODE
LABEL PROPERTY

18. NEO4J USE CASES
Real Time Recommendations
Master Data Management
Fraud Detection
Identity & Access Management
Graph Based Search
Network & IT-Operations

19. NEO4J USE CASES
Real Time Recommendations
Master Data Management
Fraud Detection
Identity & Access Management
Graph Based Search
Network & IT-Operations
GRAPH THINKING:
Real Time Recommendations
VIEWED
VIEWED
BOUGHT
VIEWED
BOUGHT
BOUGHT
BOUGHT
BOUGHT

20. NEO4J USE CASES
Real Time Recommendations
Master Data Management
Fraud Detection
Identity & Access Management
Graph Based Search
Network & IT-Operations
GRAPH THINKING:
Master Data Management
MANAGES
MANAGES
LEADS
REGION
M
ANAG
ES
MANAGES
REGION
LEADS
LEADS
COLLABORATES

21. NEO4J USE CASES
Real Time Recommendations
Master Data Management
Fraud Detection
Identity & Access Management
Graph Based Search
Network & IT-Operations
GRAPH THINKING:
Fraud Detection
O
PENED_ACCO
UNT
HAS
IS_ISSUED
HAS
LIVES
LIVES
IS_ISSUED
OPENED_ACCOUNT

22. GRAPH THINKING:
Graph Based Search
NEO4J USE CASES
Real Time Recommendations
Master Data Management
Fraud Detection
Identity & Access Management
Graph Based Search
Network & IT-Operations
PUBLISH
INCLUDE
INCLUDE
CREATE
CAPTURE
IN
IN
SOURCE
USES
USES
IN
IN
USES
SOURCE
SOURCE

23. NEO4J USE CASES
Real Time Recommendations
Master Data Management
Fraud Detection
Identity & Access Management
Graph Based Search
Network & IT-Operations
BROWSES
CONNECTS
BRIDGES
ROUTES
POWERS
ROUTES
POWERS
POWERS
HOSTS
QUERIES
GRAPH THINKING:
Network & IT-Operations

24. GRAPH THINKING:
Identity And Access Management
NEO4J USE CASES
Real Time Recommendations
Master Data Management
Fraud Detection
Identity & Access Management
Graph Based Search
Network & IT-Operations
TRUSTS
TRUSTS
ID
ID
AUTHENTICATES
AUTHENTICATES
O
W
NS
OWNS
CAN_READ

26. Why?
+

27. The Traditional Approach Towards Data

28. SYSTEMS OF RECORD

29. RDBMS
SYSTEMS OF RECORD

30. HR-tools Supply Payments Logistics CRM Support
TRADITIONAL DATA STRUCTURE
RDBMS RDBMS RDBMSRDBMS RDBMS RDBMS

31. SHIFT TOWARDS SYSTEMS OF ENGAGEMENT

32. Users Engaging With DevicesUsers Engaging With Users Devices Engaging With Devices
SYSTEMS OF ENGAGEMENT

33. SHIFT TOWARDS SYSTEMS OF ENGAGEMENT
You are here!
Data volume

34. SYSTEMS OF RECORD
Relational Database Model
Structured
Pre-computed
Based on rigid rules
SYSTEMS OF ENGAGEMENT
NoSQL Database Model
Highly Flexible
Real-Time Queries
Highly Contextual

35. http://bigdata-blog.com/nosql-definition

37. Polyglot Persistence

38. Polyglot Persistence
• Different types of data in different ways
• Take advantage of strengths of different databases
http://martinfowler.com/bliki/PolyglotPersistence.html

39. Polyglot Persistence
Functionality Database type
Shopping Cart Rapid session
reads / writes
Key-value store
Orders / Product
Catalog
Frequent reads Document
Customer social
graph
Recommendation Graph
http://www.jamesserra.com/archive/2015/07/what-is-polyglot-persistence/

40. Data Storage and
Business Rules Execu5on
Data Mining
and Aggrega5on
Applica'on
Graph Database Cluster
Neo4j Neo4j Neo4j
Ad Hoc
Analysis
Bulk Analy'c
Infrastructure
Hadoop, EDW …
Data
Scien'st
End User
Databases
Rela5onal
NoSQL
Hadoop

41. Added Complexity

42. Challenge #1: Data Sync

43. MIGRATE
ALL DATA
MIGRATE
SUBSET
DUPLICATE
SUBSET
Non-Graph Queries Graph Queries
Graph Queries Non-Graph Queries
All Queries
Rela3onal
Database
Graph
Database
Application
Application
Application
Non Graph
Data
All Data
?

46. Course Catalog
Browse & Search
• Good use-case for a document
database

48. https://github.com/johnymontana/CourseCatalog

49. Course Catalog
Browse & Search
• Good use-case for a document
database

52. Graph Based Recommendations

53. Graph Based Recommendations

54. Graph Based Recommendations

56. ?

57. Option 1: APOC Procedures

58. https://github.com/neo4j-contrib/neo4j-apoc-procedures

59. Java Stored Procedures
User-defined procedures are written in Java,
deployed into the database, and called from Cypher.
http://neo4j.com/docs/developer-manual/current/#procedures

60. Built-in Procedures

61. Built-in Procedures

62. User-defined Procedures
https://github.com/neo4j-examples/neo4j-procedure-template

63. Apoc Procedures
https://github.com/neo4j-contrib/neo4j-apoc-procedures

64. THERE’S A
PROCEDURE
FOR THAT
https://github.com/neo4j-contrib/neo4j-apoc-procedures

65. https://github.com/neo4j-contrib/neo4j-apoc-procedures/blob/master/readme.adoc

66. https://neo4j-contrib.github.io/neo4j-apoc-procedures/
#_loading_data_from_web_apis_json_xml_csv

67. ?

68. https://docs.mongodb.com/ecosystem/tools/http-interfaces/

75. Option 2: Neo4j Doc Manager

76. Neo4j Doc Manager
• Automatically sync documents from MongoDB to Neo4j
• Convert documents into graph model
http://neo4j.com/developer/mongodb/

77. Neo4j Doc Manager
Automatically sync documents from MongoDB to Neo4j

78. Document to property graph
{
"session": {
"title": "12 Years of Spring: An Open Source Journey",
"abstract": "Spring emerged as a core open source
project in early 2003 and evolved to a broad portfolio of
open source projects up until 2015."
},
"topics": [
"keynote",
"spring"
],
"room": "Auditorium",
"timeslot": "Wed 29th, 09:30-10:30",
"speaker": {
"name": "Juergen Hoeller",
"bio": "Juergen Hoeller is co-founder of the Spring
Framework open source project.",
"twitter": "https://twitter.com/springjuergen",
"picture": "http://www.springio.net/wp-content/
uploads/2014/11/juergen_hoeller-220x220.jpeg"
}
}

79. {
"session": {
"title": "12 Years of Spring: An Open Source Journey",
"abstract": "Spring emerged as a core open source
project in early 2003 and evolved to a broad portfolio of
open source projects up until 2015."
},
"topics": [
"keynote",
"spring"
],
"room": "Auditorium",
"timeslot": "Wed 29th, 09:30-10:30",
"speaker": {
"name": "Juergen Hoeller",
"bio": "Juergen Hoeller is co-founder of the Spring
Framework open source project.",
"twitter": "https://twitter.com/springjuergen",
"picture": "http://www.springio.net/wp-content/
uploads/2014/11/juergen_hoeller-220x220.jpeg"
}
}
Document to property graph

80. https://github.com/neo4j-contrib/neo4j_doc_manager

81. Demo

82. Using Data Relationships for
Recommendations
Content-based filtering
Recommend items based on what
users have liked in the past
Collaborative filtering
Predict what users like based on the
similarity of their behaviors,
activities and preferences to others
Movie
Person
Person
RATED
SIMILARITY
rating: 7
value: .92

87. Challenge #2: Operations

88. http://neo4j.com/developer/docker/

89. https://hub.docker.com/_/neo4j/
docker pull neo4j
Official Neo4j Docker Image

90. https://www.docker.com/products/docker-compose

91. docker-compose.yml

93. Resources

94. http://neo4j.com/blog/couchbase-jdbc-integrations-neo4j-3-0/
Couchbase + Neo4j integration

95. http://neo4j.com/developer/
Neo4j Developer Resources

96. Neo4j Integrations http://neo4j.com/developer/integration/
Neo4j + MongoDB http://neo4j.com/developer/mongodb/
Neo4j Doc Manager https://github.com/neo4j-contrib/neo4j_doc_manager

97. Questions?
@lyonwj
will@neo4j.com