This document introduces Couchbase 4.5 and Couchbase Mobile 1.2 and discusses several use cases for using Couchbase as a NoSQL database solution. It summarizes five common use cases: 1) high-availability caching to speed up database operations, 2) using Couchbase as a session store, 3) creating a globally distributed user profile store, 4) aggregating data from various sources, and 5) storing and accessing content and metadata.

1. Introduction to NoSQL –
Couchbase 4.5 and Couchbase
Mobile 1.2
Cécile Le Pape
Solutions Architect

2. High-Availability Caching
RDBMS
Application LayerUser Requests
Cache Misses and Write Requests
Read-Write Requests
Couchbase
Distributed Cache
Use Case 1

3.  Application objects
 Popular search query results
 Session information
 Heavily accessed web landing
pages
High-Availability Caching
 Speed up RDBMS
 Consistently low response times
for document / key lookups
 High-availability 24x7x365
 Replacement for entire caching tier
Data cached in Couchbase? Application characteristic
Use Case 1
http://www.Look.PopularSearchWuerycom
Look Something Search
WEB % of clicks % of clicks
something 56.3 28
DoSomething.com 13.4 25.08
SomethingFishy.org 9.8 14.68
Popular

4. Use Case 2
Session Store

5. Session Store
 Extremely fast access to session data
using unique session ID
 Easy scalability to handle fast growing
number of users and user-generated
data
 Always-on functionality for global
user base
Application characteristic
Use Case 2
 Session values or Cookies
(stored as key-value pairs)
 Examples include: items in a shopping
cart, flights selected, search results,
etc.
Data stored in Couchbase?

6. Use Case 3
Globally Distributed User Profile Store

7. http://www.ProfileStore.com
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Welcome back Laura!
You have 3 items in your shopping cart
waiting for you.
LOGIN
ID:
PASS:
Globally Distributed User Profile Store
 Extremely fast access to individual profiles
 Always online system as multiple
applications access user profiles
 Flexibility to add and update user
attributes
 Easy scalability to handle fast growing
number of users
 User profile with unique ID
 User setting / preferences
 User’s network
 User application state
Data stored in Couchbase? Application characteristic
Use Case 3
Laura930
********

8. Data Aggregation
 Flexibility to store any kind of content
 Flexibility to handle schema changes
 Full-text Search across data set
 High speed data ingestion
 Scales horizontally as more content gets
added to the system
 Social media feeds: Twitter, Facebook,
LinkedIn
 Blogs, news, press articles
 Data service feeds: Hoovers, Reuters
 Data form other systems
Data stored in Couchbase? Application characteristic
Use Case 4
in
F
t
NEWS
Blog

9. Use Case 5
Content and Metadata
Nature, Field, Summer, Farm, Sky, Environment, Landscaped, Gr
ass, Green,Blue, Oilseed,
Rape, Agriculture, Scenics, Land, Spring, Non-Urban
Scene,Environmental, Conservation, Sun, Meadow, Horizon,
Season, Cloud, Landscapes, Travel Locations, Pasture, Cultivated
Land, Stratoshpere, cloudy day, Oliseed Rape, Rural
Scene, Vibrant Color, No People, Beauty In Nature,Gold, Color
Image, Beauty, Idyllic, Multicolored, Yellow, Colors, Cloudscape,
Outdoors, Plant, Sunlight, Horizon Over Land
Content and metadata store

10. Content and Metadata Store
 Flexibility to store any kind of content
 Fast access to content metadata (most
accessed objects) and content
 Full-text Search across data set
 Scales horizontally as more content gets
added to the system
 Content metadata
 Content: Articles, text
 Landing pages for website
 Digital content: eBooks, magazine,
research material
Data stored in NoSQL? Application characteristic
Use Case 5
http://www.LandingPage.com
ebook
Mag

11. Macro Trends Driving NoSQL Technology
NoSQL
+ +
More Data More Users Interactive Apps

12. Why The Digital Economy Needed A New Database Solution
Question: What are the biggest problems with Relational Database that are driving adoption of
NoSQL?
LACK OF
FLEXIBILITY/ HAS
RIGID SCHEMAS
INABILITY
TO SCALE OUT
PERFORMANCE
CHALLENGES
49%
69%
50%
47%
44%
COST
ALL OF THE ABOVE
35%
29%
16%
12%

13. Agile Development
Hotel Descriptions
Reviews
User Profiles
Reviews points
to users
Hotels points
to reviews
{
“ID”: 1,
“NAME”: “Fairmont
San Francisco”,
…}
{
“REVIEW_ID”: 1,
“REVIEW”: “Loved
Hotel…”,
…}
{
“REVIEW_ID”: 2,
“REVIEW”: “Nice,
but …”,
…}
{
“USER_ID”: 1,
“DISPLAY”: “Ted’s
Trip…”,
…}
{
“USER_ID”: 2,
“DISPLAY”:
“WhatWhat …”,
…}
Must support flexible schemas to make development agile

14. Must Dynamically Scale Apps to Support Millions of Users
Scalability
RDBMS Scales Up
Get a bigger, more complex server
Users
Application Scales Out
Just add more commodity web servers
Users
System Cost
Application Performance
System Cost
Application Performance
Won’t
scale
beyond
this point

15. Consumers & Employees Demand Highly Responsive Apps
Performance
Application
layer
RDBMSCache Application
layer
RDBMSCacheCouchbase

16. Apps Must Now Stay Online 24 x 365
Availability
PERFORMANCE
JSON
JSON
JSON
JSONJSON
24/7
http://www.mypage.com
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Well, this is embarrassing.
We are having some difficulties and we apologies for the inconvenience.

17. NoSQL Considerations

18. NoSQL Considerations
Accessing data
– No standards exist yet
– Typically via SDKs or over HTTP
– Check if the programing language of your choice
is supported.
App Server
App Server
App Server
Consistency
– Consistent only at the document level
– Most documents stores currently don’t support multi-
document transactions
– Analyze your application needs
Availability
– Each node stores active and replica data
(Couchbase)
– Each node is either a master or slave (MongoDB)

19. NoSQL considerations
Operations
– Monitoring the system
– Backup and restore the system
– Upgrades and maintenance
– Support
App Server
App Server
Client
Ease of Scaling
– Ease of adding and reducing capacity
– Single node type
– App availability on topology changes
Indexing and Querying
– Secondary indexes
– Aggregates Grouping
– Basic querying / Ad hoc querying

20.  3rd party or user defined structure (Twitter feeds)
 Support for unlimited data growth (Viral apps)
 Data with non-homogenous structure
 Need to quickly and often change data structure
 Variable length documents
 Sparse data records
 Hierarchical data
Where is NoSQL a good fit?

21.  Low latency critical (ex. 1millisecond)
 High throughput (ex. 200000 ops / sec)
 Large number of users
 Unknown demand with sudden growth of users/data
 Predominantly direct document access
 Read / Mixed / Write heavy workloads
Where is NoSQL a good fit?
21©2014 Couchbase, Inc.

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Why Couchbase

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Key Capabilities
• Multiple data models
• N1QL - SQL-Like query
language
• Multiple indexes
• SDKs, ODBC / JDBC
drivers and frameworks
• Push-button scalability
• Consistent high-performance
• Always on 24x7 with HA - DR
• Easy Administration with Web UI,
Rest API and CLI
Combines the Flexibility of JSON, the Power of SQL and the Scale of
NoSQL

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Couchbase Server Defined
Couchbase Server is the first NoSQL database that enables
you to develop with agility and operate at any scale.
Managed Cache Key-Value Store Document
Database
Embedded
Database
Sync Management

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Digital Economy customers
 1 billion+ user profiles
 Replication across
7 data centers
 740 server nodes
 300K reads, 20K writes
/ sec, sustained
 50M Unique
monthly visitors
 2.5B Monthly page
views
 Replaced SQL Server
and MongoDB
 12TB data
 16M entries every
five minutes
 400K ops/sec. on
four nodes
 1 billion+ documents
 10TB+ data
 Sub-2ooms
response time

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Develop With Agility

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The Power Of The Flexible JSON Schema
Ability to store data in multiple ways
• Denormalized single document, as opposed to normalizing data across multiple table
• Dynamic Schema to add new values when needed

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Accessing Data From Couchbase
Key access using Document
ID
• Operations are extremely fast
with consistent low latency
• Reads and writes are evenly
distributed across Data
Service nodes
• Data is cached in built-in
Managed Caching layer and
stored in persistent storage
layer
Queries using N1QL
• SQL-like : SELECT *
FROM
WHERE/LIKE/GROUP/etc.,
• JOINs
• Powerful Extensions (nest,
unnest) for JSON to
support nested and
hierarchical data structures.
• Multiple access paths –
Views and global
secondary indexes
Views using static queries
• Pre-computed complex
Map-Reduce queries
• Incrementally updated to
power analytics, reporting
and dashboards
• Strong for complex custom
aggregations

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Application To Database Interaction

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N1QL, next generation NoSQL query language
• SQL-like : SELECT * FROM WHERE/LIKE/GROUP/etc.,
• JOINS
• Powerful Extensions (nest, unnest) for JSON to support nested
and hierarchical data structures.
• Multiple access paths – Views and global secondary indexes
• ODBC/JDBC drivers available

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How A JOIN In N1QL Works

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How A JOIN In N1QL Works

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How A JOIN In N1QL Works

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Couchbase Global Indexing Service
• Indexes partitioned
independently from data
• Scaled independent of data
• ForestDB storage engine
cbq> CREATE INDEX purch_customID on purchases(customerID);
cbq> CREATE INDEX purch_type on purchases(type);

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Operate At Any Scale

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Storing And Retrieving Documents

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Couchbase Architecture
• Data Service – builds and maintains
Distributed Secondary Indexes
(MapReduce Views)
• Indexing Engine – builds and
maintains Global Secondary
Indexes
• Query Engine – plans, coordinates,
and executes queries against either
Global or Distributed Indexes
• Cluster Manager – configuration,
heartbeat, statistics, RESTful
Management interface

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Data Service: Writes And Cache Management
APPLICATION SERVER
MANAGED CACHE
DISK
DISK
QUEUE
DOC 1
DOC 2DOC 3DOC 4DOC 5
DOC 1
DOC 2 DOC 3 DOC 4 DOC 5
REPLICATION/
XDCR/
CONNECTORS/
VIEWS/
INDEXING

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Query Execution Flow
1. Application submits
N1QL query
2. Query is parsed,
analyzed and plan is
created
1
2

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Query Execution Flow
3. Query Service makes
request to Index
Service
4. Index Service returns
document keys and
data
3
4

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Query Execution Flow
5. If Covering Index, skip
step 6
6. If filtering is required,
fetch documents from
Data Service56

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Query Execution Flow
7. Apply final logic (e.g.
SORT, ORDER BY)
8. Return formatted
results to application
7
8

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Couchbase Clustering Architecture

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Auto Sharding – Bucket And vBuckets
 A bucket is a logical, unique key space
 Multiple buckets can exist within a single cluster of nodes
 Each bucket has active and replica data sets
(1, 2 or 3 extra copies)
 Each data set has 1024 Virtual Buckets (vBuckets)
 Each vBucket contains 1/1024th portion of the data set
 vBuckets do not have a fixed physical server location
 Mapping between the vBuckets and physical
servers is called the cluster map
 Document IDs (keys) always get hashed to the
same vbucket
 Couchbase SDK’s lookup the vbucket ->
server mapping

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Cluster Map

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Cluster Map

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Data Services – Sharding and Replication
ACTIVE ACTIVE ACTIVE
REPLICA REPLICA REPLICA
Couchbase Server 1 Couchbase Server 2 Couchbase Server 3
ACTIVE ACTIVE
REPLICA REPLICA
Couchbase Server 4 Couchbase Server 5
SHARD
5
SHARD
2
SHARD SHARD
SHARD
4
SHARD SHARD
SHARD
1
SHARD
3
SHARD SHARD
SHARD
4
SHARD
1
SHARD
8
SHARD SHARD SHARD
SHARD
6
SHARD
3
SHARD
2
SHARD SHARD SHARD
SHARD
7
SHARD
9
SHARD
5
SHARD SHARD SHARD
SHARD
7
SHARD
SHARD
6
SHARD
SHARD
8
SHARD
9
SHARD
READ/WRITE/UPDATE
Application has single
logical connection to
cluster (client object)
• Multiple nodes added or
removed at once
• One-click operation
• Incremental movement of
active and replica
vBuckets and data
• Client library updated via
cluster map
• Fully online operation, no
downtime or loss of
performance
• Strong Consistency
enforced at document
level

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Modern Architecture – Multi-Dimensional Scaling
MDS is the architecture that enables independent scaling
of data, query, and indexing workloads while being
managed as one cluster.

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Modern Architecture – Multi-Dimensional Scaling

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Modern Architecture – Multi-Dimensional Scaling

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XDCR: Cluster Topology Aware

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XDCR: Cluster Topology Aware

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What’s new in Couchbase 4.1
Simplified
Development
Connected
Bigdata
Experience
Improved
Performance
Simplified
Security
Compliance
Improved HA &
DR
Easy Admin
Simplified Familiar
and Flexible Query
with N1QL
Full SQL Syntax
through N1QL
(INSERT/UPDATE/
DELETE and MERGE)
Integrated BI with
ODBC/JDBC
Spatial Queries for
Location Aware
Applications
New Frameworks
and Languages
(LINQ,Spring, Go)
Surround Big-data
- Spark SQL
- Spark Streams
- Kafka,
- Sqoop,
- Elastic,
- SOLR
Faster Queries with
Covering Indexes
Prepared Statements
for Low Latency
query execution
Independent Scaling
with Multi-
dimensional Scaling
Global Secondary
Indexes for Snappy
Queries
Faster Reporting and
Interactive Analytics
with Views Queries
…and more
Integrated Enterprise
Identity
Management with
LDAP Integration
Security Forensics
with Admin Auditing
Improved Data
Protection with
Lower latency XDCR
High Performance
Global Data
Distribution with
XDCR Filtering
Deployment with
High Performance
Containers: Docker
Expanded Public and
Private Cloud
Support
- AWS,
- Google,
- Azure,
- Joyent,
- Cisco,
- Verizon
New Enterprise
Platforms
- SUSE
- Oracle Ent.Linux

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What’s new in Couchbase 4.5
Simplified
Development
Improved
Performance
Improved
HA & DR
Simplified
Security
Compliance
Easy
Dev-Ops
• Simplified N1QL Query
Development with
Integrated Query
Workbench and Powerful
Query Shell
• Sub-Document Updates
for Improved
Performance and
Efficiency
• Batch Mutations through
N1QL (INSERT, UPDATE,
DELETE and MERGE)
• Integrated Full-text
Search [Preview]
• Memory-Optimized
Global Indexes for Snappy
Queries
• High Performance Read-
Your-Own-Write
Consistency with N1QL
• Faster Array operations
with Powerful Array
Indexing
• Extended JOIN
Operations for flexible
cross document
operations
• Faster Queries with
Covering Indexes &
Prepared Statements
• Improved Compaction
Management with
Circular Reuse
• High Scale
Backup/Restore for the
Enterprise
• Last Writer Wins Conflict
Resolution with XDCR
[Preview]
• Role Based Access Control
for Admins
• Certificate Based
Encryption (X509 Certs)
• Docker Support:
Deployment with High
Performance Containers
• Support for Debian 8 and
RedHat Openshift
• Enhanced Clustering for
Large Clusters (>100
Nodes)

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Couchbase Mobile

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What Is Couchbase Mobile?
• Faster development cycles
• Less long term maintenance than
traditional solutions
• Enterprise class mobile/embedded NoSQL
database + sync platform
• Fast and consistent access to data
• Removed continual network dependency

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What’s new in Couchbase Mobile 1.2
 Sync Gateway new features
– POST /{db}/_compact
– POST /{db}/_purge
– POST /{db}/_offline
– POST /{db}/_online
 Sync Gateway internally backed up by CBGT
 Couchbase Lite
– ForestDB Storage Engine (Developer Preview) - Preview the speed of our
new ForestDB storage engine.
– Database Encryption - AES-256 on-disk encryption with your choice of
provided storage library: SQLCipher or ForestDB.
– Improved Performance - Sync protocol enhancements, compression
optimizations, and lower memory usage

58. Thank you
Q&A