Couchbase Server 4.0 is both a document and a key-value data store. In this talk, I detail the steps for designing an efficient data model for Couchbase Server with examples that demonstrate when referencing vs embedding is the right choice. I also walk through how N1QL, the new SQL-like query language for JSON data, makes it easy to reshape the data into the format your application excepts without friction.

1. Data Modeling
with Couchbase Server 4.0
Cihan Biyikoglu | Dir. Product Management, Couchbase

2. ©2015 Couchbase Inc. 2
Agenda
• What is Data Modeling?
• Couchbase Server Data Models
• Documents with JSON and Key-Values
• Phase I - Logical data modeling
• Entitles,Attributes and Relationships
• Phase II - Physical data modeling
• Keys, Documents/Values, Attributes and Buckets
• Relationships
• Evolving Data Models
• Q&A

3. ©2015 Couchbase Inc. 3
What is Data Modeling?
 Data Modeling:
Exploring Structure of Data that best fit your apps needs
Modeling Cities: Buildings, ports, roads and more
Modeling Investments: Instruments, investors, orders and more
ModelingTravel Documents:Airlines, hotels, rental cars, travellers and
more

4. ©2015 Couchbase Inc. 4
Couchbase Server Data Models

5. ©2015 Couchbase Inc. 5
Couchbase Server Data Models
 Documents with JSON
– Represent complex entities with
full modeling and query flexibility
Ex: purchase order, travel itinerary
{
“Name”: “Pike Brewing”,
“Addresses”: [
{ “Loc_Identifier”:”HQ”,
“Street”:”1 pike place market st”,
“City”: “Seattle”
…},
{
“Loc_Identifier”:”Bellevue”,
…
}
],
“Founders”:…
“EstablishedData”:…
…
}
Brewery_Pike_Brewing
 Key-Value
– Represent simple entities with fast
& direct access
Ex: passwords, session-state, private/public keys
0xAB635FF987234789BC987D987EE89
7723498765
pwd_userid_00001Key
Value

6. ©2015 Couchbase Inc. 6
Logical Data Model

7. ©2015 Couchbase Inc. 7
Logical Data Modeling
 Phase I – define entities, attributes and their relationships
– Entities: Main objects that are targets of your apps operates on
• Attributes: properties that your applications keep track of for the entity
• Relationships: definition connections to other entities - 1-1, 1-many, many-many
Satellites
Instruments
Measurements
Missions
Manufacturers

8. ©2015 Couchbase Inc. 8
Physical Data Model

9. ©2015 Couchbase Inc. 9
Physical Data Model
 Phase II – Map entities, attributes and their relationships to containers
provided by the underlying database solution
Relational Databases Couchbase Server
Databases Buckets
Tables Documents with type designator attributeOR
Buckets
Rows Items (Key-Value or Key-Document)
Columns Attributes
Index Index

10. ©2015 Couchbase Inc. 10
Physical Data Modeling
 Entities > Buckets, Keys & Items
– Buckets: group of items with controls for HA, Security and Computational
Resources
• Replica count, compaction schedule, RAM quota and more
– Keys: unique identifier for instances of the entity
• Composite or Surrogate
– Items
• JSON Documents with Attributes:
 Basic types: bool, string, numeric, date or array of these types
 Embedded JSON Documents or array of embedded of these types
• BinaryValues:
 Anything up to 20MB

11. ©2015 Couchbase Inc. 11
Remember our logical data modeling?
Satellites
Instruments
Measurements
Missions
Manufacturers

12. ©2015 Couchbase Inc. 12
Physical Data Modeling
 Physical Data Model
Satellites
{
“name”:…,
“route”:…,
“missions”:[
{“name”:“launch”,
“date”:…,},
{“name”:”repair-1”,
“date”:…,}
…],
“instruments”:[
{“id”:“camera_01”},
{“id”:”altimeter_01”},
…],
“manufacturer”:{
“name”:”Boeing”,
“city”:”Seattle”,…},
…
}
Instruments
{
“id”:”camera_01”,
“manufacturer”:{
“name”:”Boeing”,
“city”:”Seattle”,…},
…}
InstrumentIDs
Measurements
{
“instrument_ id”:”altimeter_01”,
“satellite_name”:…,
“date_time”:…,
“location”:{
“lat”:…,“long”:…},
“measurement”:…
…}
ManufacturerMissions

13. ©2015 Couchbase Inc. 13
Embedding vs Referencing
 Embed When
– Both docs are frequently access
together.
– You need strict consistency between
both docs.
 ReferenceWhen
– Both docs aren’t frequently access
together.
– You need strict consistency for the
referenced information
– Need to optimize for performance
and referenced doc is large

14. ©2015 Couchbase Inc. 14
References: SQL JOINs with Couchbase Server 4.0
 Note: References are flexible in
N1QL
SELECT AVG(m.measurement),…
FROM Measurements m
JOIN Satellites s
ON KEYS m.satellite_name
WHERE m.date_time BETWEEN … AND
NOW();

15. ©2015 Couchbase Inc. 15
Relationships
 1-1
– Embed Example: Satellite and Manufacturer
 1-Many
– Embed Example: Satellite and Missions
– Reference Example: Satellite and Instruments
 Many-Many
– Reference Example: Satellite and Measurements

16. ©2015 Couchbase Inc. 16
Evolving Data Models

17. ©2015 Couchbase Inc. 17
Evolving Data Models
Change your apps code and you are good to go!
 Schema is App Driven in Couchbase Server
– OK to maintain multiple versions of the schema
 Schema Changes with Couchbase Server
– No Explicit Server Action Required by DBA
– No Downtime required to update existing data to new shape

18. ©2015 Couchbase Inc. 18
Recap
 Couchbase Server support key-value and document based data
modeling natively.
 Model data in 2 phases
– Logical data model
– Physical data model
• Embed vs Reference
 Evolve your Schema without pain

19. Get Started with Couchbase Server 4.0 - Couchbase.com/Downloads
Q&A
Cihan Biyikoglu | cihan@couchbase.com | @cihangirb