"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
Couchbase overview033113long
1. 1
Jeff
Harris
Business
Development
NoSQL
Document
Database
Data
Management
for
Interac6ve
Applica6ons
2. 2
Couchbase
NoSQL
Leadership
Leading
NoSQL
database
company
Open
Source
development
&
business
model
Most
mature,
reliable
and
widely
deployed
solu6on
>7,500
paid
producAon
deployments
worldwide
Headquarters
in
Silicon
Valley
(Mountain
View,
CA)
~120
employees
including
>70
in
engineering/product
>80%
of
commits
to
Couchbase,
memcached,
Apache
CouchDB
Document-‐oriented
NoSQL
database
Focused
on
interacAve
internet
and
mobile
applicaAons
Provide
more
flexible,
higher
performance,
more
scalable
database
than
rela6onal
alterna6ve
3. 3
Market
Adop6on
Internet
Companies
Enterprises
• Social
Gaming
• Ad
Networks
• Social
Networks
• Online
Business
Services
• E-‐Commerce
• Online
Media
• Content
Management
• Cloud
Services
• CommunicaAons
• Retail
• Financial
Services
• Health
Care
• AutomoAve/Airline
• Agriculture
• Consumer
Electronics
• Business
Systems
4. 4
Market
Adop6on
–
Customers
Internet
Companies
Enterprises
More
than
350
customers
–
7,500
produc6on
deployments
worldwide
5. 5
Use
Cases
&
Customers
Web
app
or
Use-‐case
Couchbase
Solu6on
Example
Customer
Content
Store
&
Metadata
System
Couchbase
document
store
+
ElasAc
Search
Social
Game
&
Mobile
App
Couchbase
store
game
and
player
data
Ad
Targe6ng
Couchbase
stores
user
informaAon
for
fast
access
User
Profile
Store
Couchbase
Server
as
a
key-‐value
store
Session
Store
Couchbase
Server
as
a
key-‐value
store
High
Availability
Caching
Tier
Couchbase
Server
as
a
memcached
Aer
replacement
Chat/Messaging
PlaYorm
Couchbase
Server
7. 7
RDBMS
Scales
Up
Get
a
bigger,
more
complex
server
Users
Applica6on
Scales
Out
Just
add
more
commodity
web
servers
Users
System
Cost
ApplicaAon
Performance
Rela6onal
Technology
Scales
Up
Rela6onal
Database
Expensive
and
disrup6ve
sharding,
doesn’t
perform
at
web
scale
System
Cost
ApplicaAon
Performance
Won’t
scale
beyond
this
point
Web/App
Server
Tier
8. 8
Couchbase
Server
Scales
Out
Like
App
Tier
NoSQL
Database
Scales
Out
Cost
and
performance
mirrors
app
6er
Users
Scaling
out
fla_ens
the
cost
and
performance
curves
Couchbase
Distributed
Data
Store
Web/App
Server
Tier
Applica6on
Scales
Out
Just
add
more
commodity
web
servers
Users
System
Cost
ApplicaAon
Performance
ApplicaAon
Performance
System
Cost
9. 9
If
Cars
Were
Stored
in
an
RDBMS…
h]p://iedei.files.wordpress.com/2012/04/mercedes-‐f1-‐car-‐disassembled.jpeg
10. 10
If
Cars
Were
Stored
in
a
Document
Database…
h]p://images.conceptcarz.com/imgxra/Mercedes-‐Benz/Mercedes-‐W03-‐F1-‐Spanish-‐GP_012-‐1680.jpg
11. 11
Rela6onal
vs
Document
Data
Model
Rela6onal
data
model
Document
data
model
CollecAon
of
complex
documents
with
arbitrary,
nested
data
formats
and
varying
“record”
format.
Highly-‐structured
table
organizaAon
with
rigidly-‐defined
data
formats
and
record
structure.
JSON
JSON
C1
C2
C3
C4
JSON
{
}
12. 12
RDBMS
Example:
User
Profile
Address
Info
1
DEN
30303
CO
2
MV
94040
CA
3
CHI
60609
IL
User
Info
KEY
First
ZIP_id
Last
4
NY
10010
NY
1
Frank
2
Weigel
2
Ali
2
Dodson
3
Mark
2
Azad
4
Steve
3
Yen
ZIP_id
CITY
ZIP
STATE
1
Frank
2
Weigel
To
get
info
about
specific
user,
you
perform
a
join
across
two
tables
13. 13
All
data
in
a
single
document
Document
Example:
User
Profile
{
“ID”:
1,
“FIRST”:
“Frank”,
“LAST”:
“Weigel”,
“ZIP”:
“94040”,
“CITY”:
“MV”,
“STATE”:
“CA”
}
JSON
=
+
14. 14
NoSQL
Database
Considera6ons
Easy
Scalability
Consistent
High
Performance
Flexible
Data
Model
Always
On
24x7x365
Grow
cluster
without
applicaAon
changes,
without
downAme
when
needed
Always
awesome
experience
for
your
applicaAon
users.
The
sun
never
sets
on
the
Internet,
your
applicaAon
needs
the
database
to
always
serve
data.
Keep
developers
producAve
and
allow
fast
and
easy
addiAon
of
new
features
JSON
JSON
JSON
JSONJSON
PERFORMANCE
15. 15
Couchbase
Server
Is
The
Complete
Solu6on
One
click
scalability
and
no
app
changes.
Sub
millisecond
latency
with
high
throughput
for
reads
and
writes.
Maintenance,
upgrades
and
cluster
resizing
all
online
without
applicaAon
downAme
JSON
document
model
with
no
fixed
schema.
✔
✔
✔
✔
Consistent
High
Performance
Flexible
Data
Model
Easy
Scalability
Always
On
24x7x365
16. 16
Couchbase
Server
Overview
Clustered
NoSQL
Document
Database
for
interacAve
applicaAons
• Easy
scalability
with
efficient
auto-‐sharding
ApplicaAon
stays
unchanged
as
cluster
size
changes
Data
replicaAon
and
node
auto-‐failover
• Consistent
high
performance
Sub
millisecond
latency
with
high
throughput
• Always-‐On
Maintenance,
upgrades
and
cluster
resizing
all
online
without
applicaAon
downAme
17. 17
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
18. 18
New
Couchbase
Server
Features
• Flexible
JSON
document
model
No
fixed
schema
for
higher
producAvity
and
less
obstacles
for
developers
• Data
indexing
and
querying
Secondary
indexes
on
JSON
documents
Simple
real-‐Ame
analyAcs
via
incremental
map-‐reduce
Connector
to
full-‐text
search
indexer
• Cross
datacenter
replica6on
Scale
your
data
beyond
a
single
data
center
19. 19
Couchbase
Demonstra6on
• Star6ng
with
4
database
nodes
under
load
• Dynamically
scaling
to
6
database
nodes
• Easy
management
and
monitoring
• JSON
indexing
and
querying
• Easy
configura6on
of
cross-‐
datacenter
replica6on
• Not
possible
any
other
database
technology
Couchbase
Servers
In
the
EC2
or
Datacenter
Web
applicaAon
server
ApplicaAon
user
XDCR
21. 21
3
3
2
Single
node
-‐
Couchbase
Write
Opera6on
Managed
Cache
Disk
Queue
Disk
ReplicaAon
Queue
App
Server
Couchbase
Server
Node
Doc
1
Doc
1
Doc
1
To
other
node
22. 22
3
3
2
Single
node
-‐
Couchbase
Update
Opera6on
Managed
Cache
Disk
Queue
ReplicaAon
Queue
App
Server
Couchbase
Server
Node
Doc
1’
Doc
1
Doc
1’
Doc
1
Doc
1’
Disk
To
other
node
23. 23
GET
Doc
1
3
3
2
Single
node
-‐
Couchbase
Read
Opera6on
Disk
Queue
ReplicaAon
Queue
App
Server
Couchbase
Server
Node
Doc
1
Doc
1
Doc
1
Managed
Cache
Disk
To
other
node
24. 24
COUCHBASE
SERVER
CLUSTER
Basic
Opera6on
• Docs
distributed
evenly
across
servers
• Each
server
stores
both
ac6ve
and
replica
docs
Only
one
server
acAve
at
a
Ame
• Client
library
provides
app
with
simple
interface
to
database
• Cluster
map
provides
map
to
which
server
doc
is
on
App
never
needs
to
know
• App
reads,
writes,
updates
docs
• Mul6ple
app
servers
can
access
same
document
at
same
6me
User
Configured
Replica
Count
=
1
READ/WRITE/UPDATE
ACTIVE
Doc
5
Doc
2
Doc
Doc
Doc
SERVER
1
ACTIVE
Doc
4
Doc
7
Doc
Doc
Doc
SERVER
2
Doc
8
ACTIVE
Doc
1
Doc
3
Doc
Doc
Doc
REPLICA
Doc
4
Doc
1
Doc
8
Doc
Doc
Doc
REPLICA
Doc
6
Doc
3
Doc
2
Doc
Doc
Doc
REPLICA
Doc
7
Doc
9
Doc
5
Doc
Doc
Doc
SERVER
3
Doc
6
APP
SERVER
1
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
APP
SERVER
2
Doc
9
25. 25
Add
Nodes
to
Cluster
• Two
servers
added
with
one-‐click
opera6on
• Docs
automa6cally
rebalance
across
cluster
Even
distribuAon
of
docs
Minimum
doc
movement
• Cluster
map
updated
• App
database
calls
now
distributed
over
larger
number
of
servers
REPLICA
ACTIVE
Doc
5
Doc
2
Doc
Doc
Doc
4
Doc
1
Doc
Doc
SERVER
1
REPLICA
ACTIVE
Doc
4
Doc
7
Doc
Doc
Doc
6
Doc
3
Doc
Doc
SERVER
2
REPLICA
ACTIVE
Doc
1
Doc
3
Doc
Doc
Doc
7
Doc
9
Doc
Doc
SERVER
3
SERVER
4
SERVER
5
REPLICA
ACTIVE
REPLICA
ACTIVE
Doc
Doc
8
Doc
Doc
9
Doc
Doc
2
Doc
Doc
8
Doc
Doc
5
Doc
Doc
6
READ/WRITE/UPDATE
READ/WRITE/UPDATE
APP
SERVER
1
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
APP
SERVER
2
COUCHBASE
SERVER
CLUSTER
User
Configured
Replica
Count
=
1
26. 26
Fail
Over
Node
REPLICA
ACTIVE
Doc
5
Doc
2
Doc
Doc
Doc
4
Doc
1
Doc
Doc
SERVER
1
REPLICA
ACTIVE
Doc
4
Doc
7
Doc
Doc
Doc
6
Doc
3
Doc
Doc
SERVER
2
REPLICA
ACTIVE
Doc
1
Doc
3
Doc
Doc
Doc
7
Doc
9
Doc
Doc
SERVER
3
SERVER
4
SERVER
5
REPLICA
ACTIVE
REPLICA
ACTIVE
Doc
9
Doc
8
Doc
Doc
6
Doc
Doc
Doc
5
Doc
Doc
2
Doc
8
Doc
Doc
• App
servers
accessing
docs
• Requests
to
Server
3
fail
• Cluster
detects
server
failed
– Promotes
replicas
of
docs
to
acAve
– Updates
cluster
map
• Requests
for
docs
now
go
to
appropriate
server
• Typically
rebalance
would
follow
Doc
Doc
1
Doc
3
APP
SERVER
1
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
APP
SERVER
2
User
Configured
Replica
Count
=
1
COUCHBASE
SERVER
CLUSTER
27. 27
XDCR:
Cross
Data
Center
Replica6on
US
DATA
CENTER
EUROPE
DATA
CENTER
ASIA
DATA
CENTER
h]p://blog.groosy.com/wp-‐content/uploads/2011/10/internet-‐map.jpg
28. 28
Cross
Data
Center
Replica6on
(XDCR)
COUCHBASE
SERVER
CLUSTER
NYC
DATA
CENTER
ACTIVE
Doc
Doc
2
SERVER
1
Doc
9
SERVER
2
SERVER
3
RAM
Doc
Doc
Doc
ACTIVE
Doc
Doc
Doc
RAM
ACTIVE
Doc
Doc
Doc
RAM
DISK
Doc
Doc
Doc
DISK
Doc
Doc
Doc
DISK
COUCHBASE
SERVER
CLUSTER
SF
DATA
CENTER
ACTIVE
Doc
Doc
2
SERVER
1
Doc
9
SERVER
2
SERVER
3
RAM
Doc
Doc
Doc
ACTIVE
Doc
Doc
Doc
RAM
ACTIVE
Doc
Doc
Doc
RAM
DISK
Doc
Doc
Doc
DISK
Doc
Doc
Doc
DISK
29. 29
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-‐Ame
analyAcs
Only
considers
changes
due
to
updated
data
• Full
Text
Search
Robust
integraAon
with
ElasAcSearch
cluster
Flexible
full
text
search
and
faceted
search
30. 30
COUCHBASE
SERVER
CLUSTER
Indexing
and
Querying
User
Configured
Replica
Count
=
1
ACTIVE
Doc
5
Doc
2
Doc
Doc
Doc
SERVER
1
REPLICA
Doc
4
Doc
1
Doc
8
Doc
Doc
Doc
APP
SERVER
1
COUCHBASE
Client
Library
CLUSTER
MAP
COUCHBASE
Client
Library
CLUSTER
MAP
APP
SERVER
2
Doc
9
• Indexing
work
is
distributed
amongst
nodes
• Large
data
set
possible
• Parallelize
the
effort
• Each
node
has
index
for
data
stored
on
it
• Queries
combine
the
results
from
required
nodes
ACTIVE
Doc
4
Doc
7
Doc
Doc
Doc
SERVER
2
REPLICA
Doc
6
Doc
3
Doc
2
Doc
Doc
Doc
Doc
8
ACTIVE
Doc
1
Doc
3
Doc
Doc
Doc
SERVER
3
REPLICA
Doc
7
Doc
9
Doc
5
Doc
Doc
Doc
Doc
6
Query
33. 33
Couchbase:
The
Complete
NoSQL
Solu6on
Easy
Scalability
Flexible
Data
Model
Always
On
24x7x365
Grow
cluster
without
applicaAon
changes,
without
downAme
when
needed
Always
awesome
experience
for
your
applicaAon
users.
The
sun
never
sets
on
the
Internet,
your
applicaAon
needs
the
database
to
always
serve
data.
Keep
developers
producAve
and
allow
fast
and
easy
addiAon
of
new
features
JSON
JSON
JSON
JSONJSON
PERFORMANCE
Consistent
High
Performance
34. 34
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
Ame
• 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
35. 35
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
acAve
documents
• Data
doesn’t
enArely
fit
into
RAM
Workload
simulaAng
realisAc
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
Ames
with
varying
throughputs
with
95%
latency
measured
• YCSB
test
workload
source
code
h]ps://github.com/Altoros/YCSB
39. 39
NoSQL
Database
Considera6ons
Easy
Scalability
Flexible
Data
Model
Always
On
24x7x365
Grow
cluster
without
applicaAon
changes,
without
downAme
when
needed
Always
awesome
experience
for
your
applicaAon
users.
The
sun
never
sets
on
the
Internet,
your
applicaAon
needs
the
database
to
always
serve
data.
Keep
developers
producAve
and
allow
fast
and
easy
addiAon
of
new
features
JSON
JSON
JSON
JSONJSON
PERFORMANCE
Consistent
High
Performance
40. 40
Couchbase:
High
throughput
that
scales
linearly
Linear
throughput
scalability
High
throughput
with
1.4
GB/sec
data
transfer
rate
using
4
servers
h]p://www.cisco.com/en/US/prod/collateral/switches/ps9441/ps9670/white_paper_c11-‐708169.pdf
41. 41
Draw
Something
“Goes
Viral”
3
Weeks
Azer
Launch
Draw
Something
by
OMGPOP
Daily
Ac)ve
Users
(millions)
Feb
2012
March
2012
42. 42
As
Usage
Grew,
Game
Data
Went
Non-‐
Linear
Draw
Something
by
OMGPOP
Daily
Ac)ve
Users
(millions)
Feb
2012
March
2012
43. 43
NoSQL
Database
Considera6ons
Easy
Scalability
Flexible
Data
Model
Always
On
24x7x365
Grow
cluster
without
applicaAon
changes,
without
downAme
when
needed
Always
awesome
experience
for
your
applicaAon
users.
The
sun
never
sets
on
the
Internet,
your
applicaAon
needs
the
database
to
always
serve
data.
Keep
developers
producAve
and
allow
fast
and
easy
addiAon
of
new
features
JSON
JSON
JSON
JSONJSON
PERFORMANCE
Consistent
High
Performance
44. 44
The
Sun
Never
Sets
on
the
Internet
h]p://personal.bgsu.edu/~tede/020522_briAshempire1360.jpg
45. 45
Always-‐On
24x7x365:
Proof
Point
Example
0
20
40
60
80
100
82
57
72
Couchbase
Data
Store
Availability
46. 46
Couchbase
Server
Is
The
Complete
Solu6on
One
click
scalability
and
no
app
changes.
Sub
millisecond
latency
with
high
throughput
for
reads
and
writes.
Maintenance,
upgrades
and
cluster
resizing
all
online
without
applicaAon
downAme
JSON
document
model
with
no
fixed
schema.
✔
✔
✔
✔
Consistent
High
Performance
Flexible
Data
Model
Easy
Scalability
Always
On
24x7x365
47. 47
Couchbase
Server
vs.
MongoDB
Easy
Scalability
Consistent,
High
Performance
Flexible
Data
Model
Always
On
24x7x365
Consistent
sub
millisecond
reads/writes;
Consistent
high
throughput
No
downAme
for
sotware
upgrades,
hardware
maintenance,
etc.
Schemaless
data
model
for
rapid
development
With
1-‐click,
horizontally
grow
cluster,
even
scale
across
datacenters
High
&
Inconsistent
latency;
Lower
throughput
Schemaless
data
model
for
rapid
development
Difficult
online
upgrade;
Not
all
maintenance
is
online
Complex
mulA-‐step
scaling,
no
write
scaling
across
data
centers
✔
✖
✔
✔
✔
✔
✖
✖
✔
48. 48
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
contenAon
Read
operaAons
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
49. 49
Couchbase
Server
vs.
Cassandra
Easy
Scalability
Consistent,
High
Performance
Flexible
Data
Model
Always
On
24x7x365
Consistent
sub-‐millisecond
reads/writes
and
high
throughput
No
downAme
for
sotware
upgrades,
hardware
maintenance,
etc.
Schemaless
data
model
for
rapid
development
With
1-‐click,
horizontally
grow
cluster,
even
scale
across
datacenters
High
and
inconsistent
latency;
medium
throughput
Very
complex
columnar
data
model
Online
upgrades
and
online
maintenance
Complex
mulA-‐step
scaling,
coarse
grain
growth
recommended
✔
✔
✔
✔
✖
✖
✖
✔
51. 51
Enterprise
vs.
Community
Edi6on
Enterprise
Edi6on
Community
Edi6on
Cost
• Free
for
pre-‐producAon
• StarAng
at
$2,499/node/yr
• Free
Produc6on
Readiness
ProducAon
Ready
• Take
open
source
snapshots
• Put
through
rigorous
QA
process,
fix
bugs
Unknown
ProducAon
Readiness
• Built
with
latest
open
source
• Undefined
quality
Technical
Support
Professional
Support
• Defined
SLAs
from
the
experts
• Immediate
hot
bug
fixes
Community/Forum
Support
• No
SLA,
unknown
response
Ames
• No
bugs
fixes
assured
in
a
Amely
manner
Best
Prac6ce
Exper6se
Broad
Best
PracAce
ExperAse
• From
working
with
100s
of
customers
ExperAse
of
community
members
• Based
on
limited
individual
experAse
Release
Support
Long-‐Tail
Release
Support
• Including
hot
bug
fixes
No
Support
for
Old
Releases
• Must
support
old
releases
yourself
License
Type
Commercial
License
• Std
license
terms,
SLA,
indemnity
Simple
“As
is”
license
Intended
Use
ProducAon
Deployments
Non-‐ProducAon
Use,
Simple
Use
Cases
52. 52
Next
Steps:
The
Path
to
Produc6on
ü
Couchbase
Overview
–
Done
2. Technical
session
• Who:
Architects/Developers
and
Couchbase
SoluAons
Architect
• Deployment
and
development
best
pracAces
• OperaAons
deep-‐dive
• Tech
Q&A
3. Design
review
• Review
and
feedback
on
design
and
feature
usage
• Verify
assumpAons
and
use
of
Couchbase
APIs
4. Produc6on
deployment
55. 55
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,
applicaAons
can
be
available
24x7x365
• All
nodes
are
iden6cal
Easy
provisioning
on
all
supported
plaxorms:
Linux,
Windows,
MacOS
• Supported
SDKs
for
all
common
languages
Easy
adopAon
by
developers
for
Java,
.NET,
PHP,
Ruby,
C/C++
56. 56
Couchbase
performance
with
varying
document
sizes
Consistently
low
latencies
sub-‐millisecond
for
varying
documents
sizes
with
a
mixed
workload
57. 57
Enterprise
Edi6on
Subscrip6ons
Standard
Premium
Price/node
$2499
$4499
Licensing
Per
node
Per
node
Support
Hours
10
X
5
24
X
7
Hours
of
Opera6on
7am
–
5pm
Pacific
Standard
Time
N/A
Support
Channel
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
HoYixes
Yes
Yes
Technical
Alerts
Yes
Yes
h]p://www.couchbase.com/couchbase-‐support-‐and-‐subscripAons
59. 59
Challenges
with
a
Memcached
Tier
Problem
Symptoms
Couchbase
Solu6on
Cold
Cache
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
automaAcally
replicated
across
the
Couchbase
cluster,
providing
high
availability
of
data
even
on
failures
Heavy
RDBMS
Conten6on
MulAple
requests
for
data
items
that
do
not
exist
in
the
cache
results
in
sudden
shiting
of
load
to
the
relaAonal
database
causing
heavy
contenAon
By
replicaAng
data
across
the
cluster,
Couchbase
Server
provides
consistent
performance
without
shiting
load
to
the
RDBMS
layer
Lack
of
Scalability
Adding
or
removing
memcached
nodes
is
complicated
and
causes
unpredictable
applicaAon
performance
degradaAon
Auto-‐sharding
and
online
rebalancing
in
Couchbase
Server
provides
easy
non-‐
disrupAve
expansion
of
the
cluster
Complex
Monitoring
Management
of
individual
memcached
nodes
increases
the
complexity
of
operaAons
and
lacks
a
single
consistent
view
of
the
caching
layer
Couchbase
Server
provides
an
in-‐built
admin
console
for
cluster
wide
management
and
monitoring
as
well
as
RESTful
APIs
for
easy
automaAon
and
third-‐party
integraAon
60. 60
Before
and
Azer:
Replacing
Caching
Tier
with
Couchbase
Server
61. 61
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
63. 63
How
to
Prepare
Your
Social
Game
for
Massive
Growth
Published
February
2,
2012
h]p://mashable.com/2012/02/01/social-‐game-‐prepare-‐growth/
Five
days
later…
