- Traditional Relational Model - MongoDB Document Model - Associating Entities in MongoDB

1. Schema Design
Sr. Solutions Architect, MongoDB, Inc.
Jake Angerman

2. Agenda
• Traditional Relational Model
• MongoDB Document Model
• Associating Entities in MongoDB
• There will be a test at the end

3. Relational Model

4. Relational ModelThis is hard…
Long time to develop
Queries are complex
Difficult to change

5. What happens when the requirements change?

6. Hard to make changes
New
Table
New
Table
New
Column
Name Age Phone Email
New
Column

7. Have to Manage Changes in 3 Places
Application
Code
Relational
Database
Object Relational
Mapping
XML Config DB Schema

8. Relational Model

9. Developers can be more productive
Application
Code

10. Developers can be more productive
Application
Code
Rich Queries Geospatial
Text Search
Map Reduce
Aggregation

11. The Document Model

12. Key → Value store
• One-dimensional storage
• Single value is a blob
• Query on key only
• No schema
• Value can be replaced but not
updated
Key Blob

13. Relational Record
• Two-dimensional storage
• Field contains a single value
• Query on any field
• Very structured schema
• Poor data locality requires
many tables, joins,and indexes.
Primary
Key

14. MongoDB Document
_id
• N-dimensional storage
• Field can contain many values
and embedded values
• Query on any field & level
• Flexible schema
• Optimal data locality requires
fewer indexes and provides
better performance

15. Documents are easier
Relational MongoDB
{ !
first_name: "Paul",!
surname: "Miller"!
city: "London",!
location: [45.123,47.232],!
cars: [ !
{ model: "Bentley",!
year: 1973,!
value: 100000, … },!
{ model: "Rolls Royce",!
year: 1965,!
value: 330000, … }!
}!
}!

16. Terminology
MongoDB RDBMS
Document Row
Collection Table
Index Index
Embedded Document Join
Reference Foreign Key

17. Focus on data storage
Focus on data use

18. What answers do I have?
What questions do I have?

19. Modeling Data with MongoDB
business card example

20. Business Card
Contact
Address

21. Referencing
Addresses
{
_id : ,
street : ,
city : ,
state : ”,
zip_code : ,
country :
}
Contacts
{
_id : ,
name : ,
title : ,
company : ”,
phone : ,
address_id :
}

22. Embedding
Contacts
{
_id : ,
name : ,
title : ,
company : ,
address : {
street : ,
city : ,
state : ,
zip_code : ,
country :
},
phone :
}

23. Schema Flexibility – different shapes
{
_id: ,
name : ,
title : ,
company : ,
address : {
street : ,
city : ,
state : ,
zip_code :
},
phone :
}
{
_id : ,
name : ,
url : ,
title : ,
company : ,
email : ,
address : {
street : ,
city : ,
state : ,
zip_code :
}
phone : ,
fax
}

24. {
“_id”: ,
“name”: ,
“title”: ,
“company”: ,
“address”: [
{
“street”: ,
“city”: ,
“state”: ,
“zip_code”: ,
“country”:
},
{
“street”: ,
“city”: ,
“state”:
}
],
“phone”:
}
Schema Flexibility – easily changed
{
_id : ,
name : ,
title : ,
company : ,
address : {
street : ,
city : ,
state : ,
zip_code : ,
country :
},
phone :
}

25. Modeling Data with MongoDB
address book example

26. Address Book Entity-Relationship
Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitter
• name
• location
• web
• bio
1
1

27. One-to-One
Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitter
• name
• location
• web
• bio
1
1

28. contact
• twitter_id
twitter1 1
Contact
• twitter
twitter 1
Schema Design Choices
One-to-One

29. Contact
• twitter
twitter 1
You can query or index on embedded fields. For example:
db.contacts.find( {"twitter.account":"@Decameron"} )
General Recommendation
One-to-One
{
_id : 1375-12-21,
name : "Giovanni Boccaccio",
twitter : {
account : "@Decameron",
page : "https://twitter.com/RealBoccaccio"
}
}

30. One-to-Many
Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitters
• name
• location
• web
• bio
1
1

31. contact
• phone_ids: [ ]
phone1 N
Contact
• phones
phone N
Schema Design Choices
One-to-Many

32. Contact
• phones
phone N
General Recommendation
One-to-Many Few
{
_id : 1375-12-21,
name : "Giovanni Boccaccio",
twitter : {
account : "@Decameron",
page : "https://twitter.com/RealBoccaccio"
}
phone : [
work : "+39 0571-669811",
home : "+39 671-946726",
mobile : "+39 671-038747"
]
}

33. Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitters
• name
• location
• web
• bio
1
1
Many-to-Many

34. Contacts
• name
• company
• title
• phone
Groups
• name
GroupContacts
• group_id
• contact_id
Use arrays instead
X
Traditional Relational Association
Join Table
Many-to-Many

35. group
• contact_ids: [ ]
contactN N
group contact
• group_ids: [ ]N N
Duplicated data must be updated
for consistency
group
• contacts
contact
N
contact
• groups
group
N
Schema Design Choices
Many-to-Many
Reference Embed

36. group contact
• group_ids: [ ]N N
Many-to-Many
• Use case: address
book
• Contact references
groups
Reference

37. group
• contacts
contact
N
Many-to-Many
• Use case: corporate
email system
• Group embeds contacts
for performance
Embed

38. Contacts
• name
• company
• title
addresses
• type
• street
• city
• state
• zip_code
phones
• type
• number
emails
• type
• address
thumbnail
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
twitter
• name
• location
• web
• bio
N
N
N
1
1
Document model - holistic and efficient representation

39. Contact document example
{
“name” : “Gary J. Murakami, Ph.D.”,
“company” : “MongoDB, Inc.”,
“title” : “Lead Engineer”,
“twitter” : {
“name” : “Gary Murakami”, “location” : “New Providence, NJ”,
“web” : “http://www.nobell.org”
},
“portrait_id” : 1,
“addresses” :
,
“phones” :
,
“emails” :
}

40. Free training at university.mongodb.com

41. Download at mongodb.org/downloads

43. 25% off discount code: JakeAngerman