From Event to Action: Accelerate Your Decision Making with Real-Time Automation
Couchbase Overview Nov 2013
1. Data
Management
for
Interac6ve
Applica6ons
NoSQL
Document
Database
Jeff
Harris
Business
Development
1
2. Agenda
• Company
Overview
• Kinds
of
Database
Management
System
• Common
Use
cases,
When
is
NoSQL
a
good
fit?
• NoSQL
for
Mobile
Devices,
JSON
Anywhere
• Rela6onal
vs
Non-‐Rela6onal/NoSQL
• Live
Demo
• Couchbase
Technical
Overview
(under
the
hood
and
features)
2
3. Couchbase
NoSQL
Leadership
Leading
NoSQL
database
company
Open
Source
development
&
business
model
Document-‐oriented
NoSQL
database
Focused
on
interacBve
internet
and
mobile
applicaBons
Provide
more
flexible,
higher
performance,
more
scalable
database
than
rela6onal
alterna6ve
Most
mature,
reliable
and
widely
deployed
solu6on
>7,500
paid
producBon
deployments
worldwide
Headquarters
in
Silicon
Valley
(Mountain
View,
CA)
~120
employees
including
>70
in
engineering/product
>80%
of
commits
to
Couchbase,
memcached,
Apache
CouchDB
3
4. Market
Adop6on
–
Customers
Internet
Companies
Enterprises
More
than
350
customers
–
7,500
produc6on
deployments
worldwide
4
5. Market
Adop6on
Internet
Companies
•
•
•
•
•
•
•
•
Enterprises
• CommunicaBons
• Retail
• Financial
Services
• Health
Care
• AutomoBve/Airline
• Agriculture
• Consumer
Electronics
• Business
Systems
Social
Gaming
Ad
Networks
Social
Networks
Online
Business
Services
E-‐Commerce
Online
Media
Content
Management
Cloud
Services
5
6. Two
kinds
of
Database
Management
System
OLTP
/
OLTP
like
Opera6onal
Stores
Data
warehouse
or
Analy6cs
system
6
7. Adding
a
few
more
components
InteracBve
OLTP
/
OLTP
like
Opera6onal
Stores
ETL
Streaming
Data
RDBMS
Other
legacy
systems
BI
&
ReporBng
Analy6cs
Data
warehouse
7
RDBMS
Column
stores
8. NoSQL
+
Big
Data
Opera6onal
database
for
web
and
mobile
apps
with
high
performance
at
scale
Map-‐reduce
against
huge
datasets
to
analyze
and
find
insights
and
answers
8
9. Common
Use
Cases
Social
Gaming
Ad
Targe6ng
• Couchbase
stores
player
and
game
data
• Examples
customers
include:
Zynga
• Tapjoy,
Ubiso`,
Tencent
• Couchbase
stores
user
informaBon
for
fast
access
• Examples
customers
include:
AOL,
Mediamind,
Convertro
Mobile
Apps
• Couchbase
stores
user
info
and
app
content
• Examples
customers
include:
Kobo,
PlayBka
Session
store
• Couchbase
Server
as
a
key-‐
value
store
• Examples
customers
include:
Concur,
Sabre
User
Profile
Store
• Couchbase
Server
as
a
key-‐value
store
• Examples
customers
include:
Tunewiki
High
availability
cache
Content
&
Metadata
Store
• Couchbase
document
store
with
ElasBc
Search
• Examples
customers
include:
McGraw
Hill
3rd
party
data
aggrega6on
• Couchbase
stores
social
media
and
data
feeds
• Couchbase
Server
used
as
a
cache
Ber
replacement
• Examples
customers
include:
LivePerson
• Examples
customers
include:
Orbitz
9
12. JSON
Anywhere
JS
N
Couchbase
Server
Sync Gateway
Lite
Server
JS
N
JS
N
• JSON
on
the
device
• JSON
on
the
wire
Developers
increasingly
prefer
NoSQL
database
No
need
for
data
transformaBon
12
• JSON
in
the
cloud
Flexible
data
model
High
performance
Easy
scalability
14. Rela6onal
Technology
Scales
Up
Applica6on
Scales
Out
Just
add
more
commodity
web
servers
System
Cost
ApplicaBon
Performance
Web/App
Server
Tier
Users
RDBMS
Scales
Up
Get
a
bigger,
more
complex
server
System
Cost
ApplicaBon
Performance
Won’t
scale
beyond
this
point
Rela6onal
Database
Users
Expensive
and
disrup6ve
sharding,
doesn’t
perform
at
web
scale
14
15. Couchbase
Server
Scales
Out
Like
App
Tier
Applica6on
Scales
Out
Just
add
more
commodity
web
servers
System
Cost
ApplicaBon
Performance
Web/App
Server
Tier
Users
NoSQL
Database
Scales
Out
Cost
and
performance
mirrors
app
6er
System
Cost
ApplicaBon
Performance
Couchbase
Distributed
Data
Store
Users
Scaling
out
flabens
the
cost
and
performance
curves
15
16. If
Cars
Were
Stored
in
an
RDBMS…
hhp://iedei.files.wordpress.com/2012/04/mercedes-‐f1-‐car-‐disassembled.jpeg
16
17. If
Cars
Were
Stored
in
a
Document
Database…
hhp://images.conceptcarz.com/imgxra/Mercedes-‐Benz/Mercedes-‐W03-‐F1-‐Spanish-‐GP_012-‐1680.jpg
17
18. Rela6onal
vs
Document
Data
Model
C1
C2
C3
C4
{
}
JSON
JSON
JSON
Rela6onal
data
model
Document
data
model
Highly-‐structured
table
organizaBon
with
rigidly-‐defined
data
formats
and
record
structure.
CollecBon
of
complex
documents
with
arbitrary,
nested
data
formats
and
varying
“record”
format.
18
19. RDBMS
Example:
User
Profile
User
Info
Address
Info
KEY
First
Last
ZIP_id
ZIP_id
CITY
STATE
ZIP
1
Frank
Weigel
2
1
DEN
CO
30303
2
Ali
Dodson
2
2
MV
CA
94040
3
Mark
Azad
2
3
CHI
IL
60609
4
Steve
Yen
3
4
NY
NY
10010
To
get
info
about
specific
user,
you
perform
a
join
across
two
tables
19
20. Document
Example:
User
Profile
{
“ID”:
1,
“FIRST”:
“Frank”,
“LAST”:
“Weigel”,
“ZIP”:
“94040”,
“CITY”:
“MV”,
“STATE”:
“CA”
}
+
=
JSON
All
data
in
a
single
document
20
21. Making
the
Same
Change
With
a
Document
DB
{
“ID”:
1,
“FIRST”:
“Frank”,
“LAST”:
“Weigel”,
“ZIP”:
“94040”,
“CITY”:
“MV”,
“STATE”:
“CA”,
“STATUS”:
{
“TEXT”:
“At
Conf”
}
,
}
“GEO_LOC”:
“134”
},
“COUNTRY”:
”USA”
}
JSON
Just
add
informa6on
to
a
document
22. Rela6onal
vs
Document
Performance
User
Table
Photo
Table
User
ID
First
Last
Zip
1
Frank
Wiegel
Weigel
94040
2
Joe
Smith
94040
3
Ali
Dodson
94040
4
Sarah
Gorin
Bob
Young
30303
6
Nancy
Baker
10010
7
Ray
Jones
31311
8
Lee
Chen
V5V3
Photo
ID
Comment
2
d043
NYC
2
b054
Bday
5
c036
Miami
7
d072
Sunset
5002
e086
Spain
NW1
5
User
ID
Status
Table
Status
ID
Text
1
a42
At
conf
4
5
b26
c032
excited
5
4
c32
b26
hockey
12
•
•
•
User
ID
d83
Go
A’s
5000
e34
sailing
Affilia6ons
Table
5000
Doug
Moore
04252
5001
Mary
White
41694
User
ID
Affilia6ons
Affilia6ons
ID
Name
Lisa
Lisa
Clark
12425
a42
Cal
4
b96
USC
7
5002
5002
2
c14
UW
8
e22
{
{
{
{
{
{
}
}
}
JSON
JSON
}
}
JSON
JSON
}
JSON
JSON
Oxford
Faster
response
6mes
and
higher
throughput
23. NoSQL
Database
Considera6ons
Easy
Scalability
PE
RF O R M A N C E
Grow
cluster
without
applicaBon
changes,
without
downBme
when
needed
Consistent
High
Performance
Always
awesome
experience
for
your
applicaBon
users.
Always
On
24x7x365
JSON
JSON JSO
JSON N
JSON
Flexible
Data
Model
Keep
developers
producBve
and
allow
fast
and
easy
addiBon
of
new
features
The
sun
never
sets
on
the
Internet,
your
applicaBon
needs
the
database
to
always
serve
data.
23
24. Couchbase
Server
Is
The
Complete
Solu6on
✔
Easy
Scalability
Consistent
High
✔
Performance
One
click
scalability
and
no
app
changes.
Sub
millisecond
latency
with
high
throughput
for
reads
and
writes.
Always
On
✔
24x7x365
Maintenance,
upgrades
and
cluster
resizing
all
online
without
applicaBon
downBme
✔
Flexible
Data
Model
JSON
document
model
with
no
fixed
schema.
24
25. Couchbase
Server
Overview
Clustered
NoSQL
Document
Database
for
interacBve
applicaBons
• Easy
scalability
with
efficient
auto-‐sharding
ApplicaBon
stays
unchanged
as
cluster
size
changes
Data
replicaBon
and
node
auto-‐failover
• Consistent
high
performance
Sub
millisecond
latency
with
high
throughput
• Always-‐On
Maintenance,
upgrades
and
cluster
resizing
all
online
without
applicaBon
downBme
25
26. Couchbase
Server
Features
• Easy
scalability
• Built-‐in
clustering
• All
nodes
equal
• One
click
to
scale
horizontally
• Consistent
High
Performance
• Built-‐in
managed
cache
• High
performance
for
both
reads
and
writes
• Always
on
•
•
•
•
Data
replication
with
auto-‐failover
Cross
Datacenter
Replication
Zero-‐downtime
maintenance
Monitoring
and
administration
APIs
and
GUI
26
27. New
Couchbase
Server
Features
• Flexible
JSON
document
model
No
fixed
schema
for
higher
producBvity
and
less
obstacles
for
developers
• Data
indexing
and
querying
Secondary
indexes
on
JSON
documents
Simple
real-‐Bme
analyBcs
via
incremental
map-‐reduce
Connector
to
full-‐text
search
indexer
• Cross
datacenter
replica6on
Scale
your
data
beyond
a
single
data
center
27
29. Single
node
-‐
Couchbase
Write
Opera6on
App
Server
Doc
1
3
2
Managed
Cache
ReplicaBon
Queue
Doc
1
Disk
Queue
To
other
node
3
Disk
Couchbase
Server
Node
29
30. Single
node
-‐
Couchbase
Update
Opera6on
App
Server
Doc
1’
3
2
Managed
Cache
ReplicaBon
Queue
Doc
1
Doc
1’
Disk
Queue
To
other
node
3
Disk
Doc
1
Couchbase
Server
Node
30
31. App
Server
GET
Doc
1
Single
node
-‐
Couchbase
Read
Opera6on
3
2
Managed
Cache
ReplicaBon
Queue
Doc
1
Disk
Queue
To
other
node
3
Disk
Doc
1
Couchbase
Server
Node
31
32. Basic
Opera6on
APP
SERVER
1
APP
SERVER
2
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
READ/WRITE/UPDATE
SERVER
1
ACTIVE
SERVER
2
ACTIVE
• Docs
distributed
evenly
across
servers
SERVER
3
ACTIVE
• Each
server
stores
both
ac6ve
and
replica
docs
Doc
5
Doc
Doc
4
Doc
Doc
1
Doc
Doc
2
Doc
Doc
7
Doc
Doc
3
Doc
Only
one
server
acBve
at
a
Bme
Doc
9
Doc
Doc
8
Doc
Doc
6
Doc
• Client
library
provides
app
with
simple
interface
to
database
REPLICA
REPLICA
REPLICA
• Cluster
map
provides
map
to
which
server
doc
is
on
Doc
4
Doc
Doc
6
Doc
Doc
7
Doc
Doc
1
Doc
Doc
3
Doc
Doc
9
Doc
• App
reads,
writes,
updates
docs
Doc
8
Doc
Doc
2
Doc
Doc
5
Doc
• Mul6ple
app
servers
can
access
same
document
at
same
6me
App
never
needs
to
know
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
32
33. Add
Nodes
to
Cluster
APP
SERVER
1
APP
SERVER
2
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
READ/WRITE/UPDATE
SERVER
1
ACTIVE
SERVER
2
ACTIVE
READ/WRITE/UPDATE
SERVER
3
ACTIVE
Doc
5
Doc
Doc
4
Doc
Doc
1
Doc
Doc
7
Doc
Doc
3
Doc
Doc
9
Doc
Doc
8
Doc
Doc
6
SERVER
5
ACTIVE
Doc
Doc
2
SERVER
4
ACTIVE
Doc
REPLICA
REPLICA
REPLICA
Doc
4
Doc
Doc
6
Doc
Doc
7
Doc
Doc
3
Doc
Doc
9
Doc
Doc
2
Doc
Doc
5
Even
distribuBon
of
docs
Minimum
doc
movement
• Cluster
map
updated
REPLICA
Doc
Doc
8
• Docs
automa6cally
rebalance
across
cluster
Doc
Doc
1
Doc
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
• Two
servers
added
with
one-‐click
opera6on
33
REPLICA
• App
database
calls
now
distributed
over
larger
number
of
servers
34. Fail
Over
Node
APP
SERVER
1
APP
SERVER
2
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
SERVER
1
ACTIVE
SERVER
2
ACTIVE
SERVER
3
ACTIVE
SERVER
4
ACTIVE
Doc
5
Doc
Doc
4
Doc
Doc
1
Doc
Doc
9
Doc
Doc
2
Doc
Doc
7
Doc
Doc
3
Doc
Doc
8
SERVER
5
ACTIVE
Doc
Doc
1
Doc
6
Doc
Doc
Doc
3
REPLICA
REPLICA
REPLICA
REPLICA
Doc
4
Doc
Doc
6
Doc
Doc
7
Doc
Doc
5
Doc
1
Doc
Doc
3
Doc
Doc
9
Doc
Doc
Doc
2
Doc
8
Doc
Doc
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
REPLICA
34
• App
servers
accessing
docs
• Requests
to
Server
3
fail
• Cluster
detects
server
failed
– Promotes
replicas
of
docs
to
acBve
– Updates
cluster
map
• Requests
for
docs
now
go
to
appropriate
server
• Typically
rebalance
would
follow
35. XDCR:
Cross
Data
Center
Replica6on
US
DATA
CENTER
EUROPE
DATA
CENTER
ASIA
DATA
CENTER
hhp://blog.groosy.com/wp-‐content/uploads/2011/10/internet-‐map.jpg
35
36. Cross
Data
Center
Replica6on
(XDCR)
SERVER
2
ACTIVE
SERVER
1
ACTIVE
SERVER
3
ACTIVE
Doc
Doc
Doc
Doc
2
RAM
Doc
Doc
COUCHBASE
SERVER
CLUSTER
NYC
DATA
CENTER
Doc
Doc
9
Doc
RAM
Doc
DISK
Doc
Doc
Doc
RAM
Doc
Doc
Doc
DISK
Doc
Doc
DISK
SERVER
2
ACTIVE
SERVER
1
ACTIVE
SERVER
3
ACTIVE
Doc
COUCHBASE
SERVER
CLUSTER
SF
DATA
CENTER
Doc
Doc
Doc
2
RAM
Doc
Doc
Doc
Doc
9
Doc
DISK
RAM
Doc
36
Doc
Doc
Doc
DISK
RAM
Doc
Doc
Doc
Doc
DISK
Doc
37. Indexing
and
Querying
Features
• Index
and
Query
Distributed
indexing
and
querying
Secondary
indexes
of
JSON
document
content
Flexible
querying
of
indexes
• Incremental
Map-‐Reduce
Distributed
simple
real-‐Bme
analyBcs
Only
considers
changes
due
to
updated
data
• Full
Text
Search
Robust
integraBon
with
ElasBcSearch
cluster
Flexible
full
text
search
and
faceted
search
37
38. Indexing
and
Querying
APP
SERVER
1
APP
SERVER
2
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
Query
SERVER
1
ACTIVE
SERVER
2
ACTIVE
SERVER
3
ACTIVE
• Indexing
work
is
distributed
amongst
nodes
Doc
5
Doc
Doc
4
Doc
Doc
1
Doc
• Large
data
set
possible
Doc
2
Doc
Doc
7
Doc
Doc
3
Doc
• Parallelize
the
effort
Doc
9
Doc
Doc
8
Doc
Doc
6
Doc
REPLICA
REPLICA
REPLICA
Doc
4
Doc
Doc
6
Doc
Doc
7
Doc
Doc
1
Doc
Doc
3
Doc
Doc
9
Doc
Doc
8
Doc
Doc
2
Doc
Doc
5
Doc
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
38
• Each
node
has
index
for
data
stored
on
it
• Queries
combine
the
results
from
required
nodes
40. Couchbase
Demonstra6on
• Star6ng
with
4
database
nodes
under
load
• Dynamically
scaling
to
6
database
nodes
ApplicaBon
user
• Easy
management
and
monitoring
Web
applicaBon
server
• JSON
indexing
and
querying
• Easy
configura6on
of
cross-‐
datacenter
replica6on
Couchbase
Servers
In
the
EC2
or
Datacenter
• Not
possible
any
other
database
technology
40
XDCR
42. Couchbase:
The
Complete
NoSQL
Solu6on
Easy
Scalability
PE
Grow
cluster
without
applicaBon
changes,
without
downBme
when
needed
Consistent
High
Performance
RF O R M A N C E
Always
awesome
experience
for
your
applicaBon
users.
Always
On
24x7x365
JSON
JSON JSO
JSON N
JSON
Flexible
Data
Model
Keep
developers
producBve
and
allow
fast
and
easy
addiBon
of
new
features
The
sun
never
sets
on
the
Internet,
your
applicaBon
needs
the
database
to
always
serve
data.
42
43. Consistent
High
Performance
• Consistent,
predictable
sub
millisecond
latency
Apps
need
fast,
predictable
access
to
data,
it’s
not
good
enough
to
be
fast
some
of
the
Bme
• Consistent,
predictable
throughput
Throughput
capacity
of
your
data
layer
should
be
independent
of
the
mix
of
reads
and
writes
• Linear
throughput
scalability
Double
the
number
of
servers,
get
twice
the
maximum
throughput
and
double
the
data
capacity
43
44. YCSB
Benchmark
Details
• Web
applica6on
simula6on
Simulates
changing
set
of
users
using
the
app/accessing
data
Document
size
of
1.5-‐2K
with
15
million
acBve
documents
• Data
doesn’t
enBrely
fit
into
RAM
Workload
simulaBng
realisBc
mix
of
reads
and
writes
(60/40)
• System
details
4
node
cluster
with
seperate
node
to
run
client
workload
AWS
Extra
Large
instances
with
striped
EBS
1
replica
setup
(For
mongoDB
-‐
no
write
concern,
no
journaling)
Each
test
run
3
Bmes
with
varying
throughputs
with
95%
latency
measured
• YCSB
test
workload
source
code
hhps://github.com/Altoros/YCSB
44
48. NoSQL
Database
Considera6ons
Easy
Scalability
PE
Grow
cluster
without
applicaBon
changes,
without
downBme
when
needed
Consistent
High
Performance
RF O R M A N C E
Always
awesome
experience
for
your
applicaBon
users.
Always
On
24x7x365
JSON
JSON JSO
JSON N
JSON
Flexible
Data
Model
Keep
developers
producBve
and
allow
fast
and
easy
addiBon
of
new
features
The
sun
never
sets
on
the
Internet,
your
applicaBon
needs
the
database
to
always
serve
data.
48
49. Couchbase:
High
throughput
that
scales
linearly
High
throughput
with
1.4
GB/sec
data
transfer
rate
using
4
servers
Linear
throughput
scalability
hhp://www.cisco.com/en/US/prod/collateral/switches/ps9441/ps9670/white_paper_c11-‐708169.pdf
49
50. Draw
Something
“Goes
Viral”
3
Weeks
Azer
Launch
Draw
Something
by
OMGPOP
Daily
Ac)ve
Users
(millions)
Feb
2012
50
March
2012
51. As
Usage
Grew,
Game
Data
Went
Non-‐
Draw
Something
by
OMGPOP
Linear
Daily
Ac)ve
Users
(millions)
Feb
2012
51
March
2012
52. NoSQL
Database
Considera6ons
Easy
Scalability
PE
Grow
cluster
without
applicaBon
changes,
without
downBme
when
needed
Consistent
High
Performance
RF O R M A N C E
Always
awesome
experience
for
your
applicaBon
users.
Always
On
24x7x365
JSON
JSON JSO
JSON N
JSON
Flexible
Data
Model
Keep
developers
producBve
and
allow
fast
and
easy
addiBon
of
new
features
The
sun
never
sets
on
the
Internet,
your
applicaBon
needs
the
database
to
always
serve
data.
52
53. The
Sun
Never
Sets
on
the
Internet
hhp://personal.bgsu.edu/~tede/020522_briBshempire1360.jpg
53
55. Couchbase
Server
Is
The
Complete
Solu6on
✔
Easy
Scalability
Consistent
High
✔
Performance
One
click
scalability
and
no
app
changes.
Sub
millisecond
latency
with
high
throughput
for
reads
and
writes.
Always
On
✔
24x7x365
Maintenance,
upgrades
and
cluster
resizing
all
online
without
applicaBon
downBme
✔
Flexible
Data
Model
JSON
document
model
with
no
fixed
schema.
55
56. Couchbase
Server
vs.
MongoDB
Easy
Scalability
Consistent,
High
Performance
Flexible
Data
Model
Always
On
24x7x365
With
1-‐click,
horizontally
✔
grow
cluster,
even
scale
across
datacenters
Consistent
sub
millisecond
✔
reads/writes;
throughput
Consistent
high
✔
Schemaless
data
model
for
rapid
development
✔
No
downBme
for
so`ware
upgrades,
hardware
maintenance,
etc.
56
✖
Complex
mulB-‐step
scaling,
no
write
scaling
across
data
centers
✖
High
&
Inconsistent
latency;
Lower
throughput
✔
Schemaless
data
model
for
rapid
development
✖
✔
Difficult
online
upgrade;
Not
all
maintenance
is
online
57. Consistent
Lower
Latencies
and
Higher
Throughput
• Couchbase
High
read
and
write
throughput
and
consistent
low
latencies
Write
performance
advantage
due
to
low
granularity
of
Couchbase
memory
locking
mechanism
and
minimal
contenBon
Read
operaBons
happen
concurrently
with,
and
independently
of
writes
• MongoDB
Severely
limited
write
throughput
due
to
very
coarse
write
locks
that
limit
concurrency
at
the
node
level
Inconsistent
latencies
and
throughput
as
all
reads
need
to
wait
for
a
write
to
finish.
• Cost
Considera6ons
57
58. Couchbase
Server
vs.
Cassandra
Easy
Scalability
✔
With
1-‐click,
horizontally
grow
cluster,
even
scale
across
datacenters
Consistent,
High
✔
Performance
Consistent
sub-‐millisecond
reads/writes
and
high
throughput
Flexible
Data
Model
✔
Schemaless
data
model
for
rapid
development
✔
No
downBme
for
so`ware
upgrades,
hardware
maintenance,
etc.
Always
On
24x7x365
58
✖
Complex
mulB-‐step
scaling,
coarse
grain
growth
recommended
✖
High
and
inconsistent
latency;
medium
throughput
✖
Very
complex
columnar
data
model
✔
Online
upgrades
and
online
maintenance
60. Enterprise
vs.
Community
Edi6on
Enterprise
Edi6on
Cost
Community
Edi6on
• Free
for
pre-‐producBon
• StarBng
at
$2,499/node/yr
• Free
Produc6on
Readiness
ProducBon
Ready
Unknown
ProducBon
Readiness
Technical
Support
Professional
Support
Community/Forum
Support
Best
Prac6ce
Exper6se
Broad
Best
PracBce
ExperBse
ExperBse
of
community
members
Release
Support
Long-‐Tail
Release
Support
No
Support
for
Old
Releases
License
Type
Commercial
License
Simple
“As
is”
license
Intended
Use
ProducBon
Deployments
Non-‐ProducBon
Use,
Simple
Use
Cases
• Take
open
source
snapshots
• Put
through
rigorous
QA
process,
fix
bugs
• Defined
SLAs
from
the
experts
• Immediate
hot
bug
fixes
• Built
with
latest
open
source
• Undefined
quality
• No
SLA,
unknown
response
Bmes
• No
bugs
fixes
assured
in
a
Bmely
manner
• From
working
with
100s
of
customers
• Including
hot
bug
fixes
• Based
on
limited
individual
experBse
• Must
support
old
releases
yourself
• Std
license
terms,
SLA,
indemnity
60
61. Next
Steps:
The
Path
to
Produc6on
ü
Couchbase
Overview
–
Done
2. Technical
session
• Who:
Architects/Developers
and
Couchbase
SoluBons
Architect
• Deployment
and
development
best
pracBces
• OperaBons
deep-‐dive
• Tech
Q&A
3. Design
review
• Review
and
feedback
on
design
and
feature
usage
• Verify
assumpBons
and
use
of
Couchbase
APIs
4. Produc6on
deployment
61
62. Thank
you
Couchbase
NoSQL
Document
Database
62
64. Couchbase
Server
Features
• Graphical
monitoring
and
admin
console
with
RESTful
interface
Single
click
cluster
resizing,
powerful
monitoring
accessible
via
every
node
• Online
upgrades,
backups
and
database
maintenance
Database
is
always
online,
applicaBons
can
be
available
24x7x365
• All
nodes
are
iden6cal
Easy
provisioning
on
all
supported
plaxorms:
Linux,
Windows,
MacOS
• Supported
SDKs
for
all
common
languages
Easy
adopBon
by
developers
for
Java,
.NET,
PHP,
Ruby,
C/C++
64
65. Couchbase
performance
with
varying
document
sizes
Consistently
low
latencies
sub-‐millisecond
for
varying
documents
sizes
with
a
mixed
workload
65
66. Enterprise
Edi6on
Subscrip6ons
Standard
Premium
$2499
$4499
Per
node
Per
node
10
X
5
24
X
7
7am
–
5pm
Pacific
Standard
Time
N/A
Phone,
Email,
Web,
Forums
Phone,
Email,
Web,
Forums
P1
Response
Time
5
hours
2
hours
P2
Response
Time
1
day
5
hours
Update
releases
Yes
Yes
Ho{ixes
Yes
Yes
Technical
Alerts
Yes
Yes
Price/node
Licensing
Support
Hours
Hours
of
Opera6on
Support
Channel
hhp://www.couchbase.com/couchbase-‐support-‐and-‐subscripBons
66
68. Challenges
with
a
Memcached
Tier
Problem
Cold
Cache
Heavy
RDBMS
Conten6on
Lack
of
Scalability
Complex
Monitoring
Symptoms
Couchbase
Solu6on
Slowdown
or
collapse
of
the
data
service
layer
due
to
heavily
overloaded
RDBMS
when
memcached
nodes
go
down
(on
failure
or
for
maintenance)
Data
is
automaBcally
replicated
across
the
Couchbase
cluster,
providing
high
availability
of
data
even
on
failures
MulBple
requests
for
data
items
that
do
not
exist
in
the
cache
results
in
sudden
shi`ing
of
load
to
the
relaBonal
database
causing
heavy
contenBon
By
replicaBng
data
across
the
cluster,
Couchbase
Server
provides
consistent
performance
without
shi`ing
load
to
the
RDBMS
layer
Adding
or
removing
memcached
nodes
is
complicated
and
causes
unpredictable
applicaBon
performance
degradaBon
Auto-‐sharding
and
online
rebalancing
in
Couchbase
Server
provides
easy
non-‐
disrupBve
expansion
of
the
cluster
Management
of
individual
Couchbase
Server
provides
an
in-‐built
memcached
nodes
increases
the
admin
console
for
cluster
wide
complexity
of
operaBons
and
lacks
a
management
and
monitoring
as
well
as
single
consistent
view
of
the
caching
RESTful
APIs
for
easy
automaBon
and
layer
third-‐party
integraBon
68
69. Before
and
Azer:
Replacing
Caching
Tier
with
Couchbase
Server
69
70. Memcached
Tier
Replacement:
How
it
Works
• Fully
memcached
protocol
compa6ble
• Easy
to
replace
a
6er
of
individual
memcached
servers
with
a
Couchbase
Server
cluster
• The
cluster
receives
reads
and
writes,
keeps
frequently
accessed
items
in
memory,
persists
and
shards
and
replicates
the
data
amongst
the
cluster
• Reads
and
writes
are
s6ll
as
low
latency
and
high
throughput
as
memcached
• User
gets
all
the
scalability
and
high-‐availability
advantages
of
a
Couchbase
Server
cluster
70
72. How
to
Prepare
Your
Social
Game
for
Massive
Growth
Published
February
2,
2012
Five
days
later…
hhp://mashable.com/2012/02/01/social-‐game-‐prepare-‐growth/
72
