Document Data Modelling with Couchbase Server 4.0

Data Modelingwith Couchbase Server

4.0Cihan Biyikoglu | Dir. Product Management,

Couchbase

©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


What is Data Modeling? Data Modeling:

Exploring Structure of Data that best fit your apps needs

Modeling Cities: Buildings, ports, roads and moreModeling Investments: Instruments, investors, orders and moreModeling Travel Documents: Airlines, hotels, rental cars, travellers and more


Couchbase Server Data Models


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 accessEx: passwords, session-state, private/public keys

0xAB635FF987234789BC987D987EE897723498765

pwd_userid_00001Key

Value


Logical Data Model


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


Physical Data Model


Physical Data Model Phase II – Map entities, attributes and their relationships to

containers provided by the underlying database solution

Relational Databases Couchbase ServerDatabases Buckets

Tables Documents with type designator attribute OR

Buckets

Rows Items (Key-Value or Key-Document)

Columns Attributes

Index Index


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

• Binary Values: Anything up to 20MB


Remember our logical data modeling?

Satellites

Instruments

Measurements

Missions

Manufacturers


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”,…},…}

Inst

rum

ent I

Ds Measurements{ “instrument_ id”:”altimeter_01”, “satellite_name”:…, “date_time”:…, “location”:{ “lat”:…,“long”:…}, “measurement”:……}M

anuf

actu

rer

Miss

ions


Embedding vs Referencing Embed When

– Both docs are frequently access together.

– You need strict consistency between both docs.

Reference When– 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


References: SQL JOINs with Couchbase Server 4.0

Note: References are flexible in N1QL

SELECT AVG(m.measurement),…FROM Measurements m

JOIN Satellites sON KEYS

m.satellite_nameWHERE m.date_time BETWEEN … AND NOW();


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


Evolving Data Models


Evolving Data ModelsChange 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


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

Get Started with Couchbase Server 4.0 - Couchbase.com/Downloads

Q&ACihan Biyikoglu | [email protected] |

@cihangirb

mailto:[email protected]

Data & Analytics

Document Data Modelling with Couchbase Server 4.0