sdec2011 using couchbase for social game scaling and speed

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A social game, by it's very nature, can spread very quickly to a large user population. Because the game is typically interactive, the speed of retrieving information needed for the user's interactions with the system is critical. When building their new game Animal Party, the developers at Tribal Crossing needed to get away from the complexity of sharding an SQL database. They also were looking for a solution to the administration cost associated with the operation of traditional data stores. When evaluating multiple different NoSQL solutions, they realized that Couchbase's Membase server meets most of their critical requirements in developing their game software. Simple to use, Couchbase's model allows Tribal Crossing to easily model their game interactions with the key/value data store. Fast read and write performance is required with interactive, social games, and they found that support in Membase as well. Elastic scalability is easily achieved by simply adding more nodes to the Couchbase cluster without any modifications required to the application. Relying on Couchbase's technology Tribal Crossing has been able to quickly build and scale Animal Party with a small team and no dedicated system administrators.http://sdec.kr/

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Page 1: SDEC2011 Using Couchbase for social game scaling and speed

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Chiyoung Seo, Couchbase Inc. Matt Ingenthron, Couchbase Inc.

USING  COUCHBASE  FOR  SOCIAL  GAME  SCALING  AND  SPEED    

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•  Introduc-on  •  What  is  Couchbase  Server?  

–  Simple,  Fast,  Elas-c  –  Technology  Overview  (Architecture,  data  flow,  rebalancing)  

•  Tribal  Crossing  Inc:  Animal  Party  –  Challenges  before  Couchbase  

•  Original  Architecture  –  Why  Couchbase?  

•  Simplicity  •  Performance  •  Flexibility  

–  Deploying  Couchbase  •  New  Architecture  •  EC2  •  Data  Model  •  Accessing  data  in  Couchbase  

•  Product  Roadmap  •  Q&A  

Agenda  

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•  Membase  and  CouchOne  have  merged  to  form  Couchbase  Inc.  (headquartered  in  Silicon  Valley)  

•  Team  –  Brings  together  the  creators  and  core  contributors  of  Memcached,  Membase  and  CouchDB  technologies  

–  Doubles  technical  team  size,  accelerates  roadmaps  by  over  a  year  •  Products  

–  Couchbase  Server  (Formerly  Membase)  –  Couchbase  Single  Server  –  Mobile  Couchbase  (iPhone  and  Android)  

•  Technology  –  Most  mature,  reliable  and  widely  deployed  NoSQL  technologies  –  Fully  featured,  open  source  document  datastore  –  First  complete,  end-­‐to-­‐end  NoSQL  database  product  

Couchbase  Inc.  

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Modern Interactive Web Application Architecture

Application Scales Out Just add more commodity web servers

Database Scales Up Get a bigger, more complex server

www.facebook.com/animalparty  

Web  Servers  

Rela-onal    Database  

Load  Balancer  

-­‐  Expensive  and  disrup-ve  sharding  -­‐  Doesn’t  perform  at  Web  Scale  

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Couchbase  Server  is  a  distributed  database  

Couchbase  Servers  

Web    applica-on    server  

Applica-on  user  

Couchbase  Web  Console  

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Couchbase data layer scales like application logic tier Data layer now scales with linear cost and constant performance.

Application Scales Out Just add more commodity web servers

Database Scales Out Just add more commodity data servers

Scaling out flattens the cost and performance curves.

Couchbase    Servers  

www.facebook.com/animalparty  

Web  Servers  Load  Balancer  

Horizontally  scalable,  schema-­‐less,  auto-­‐sharding,  high-­‐performance  at  Web  Scale  

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Couchbase  Server  is  Simple,  Fast,  Elas-c  

•  Five  minutes  or  less  to  a  working  cluster  –  Downloads  for  Windows,  Linux  and  OSX  –  Start  with  a  single  node  –  One  bucon  press  joins  nodes  to  a  cluster  

•  Easy  to  develop  against  –  Just  SET  and  GET  –  no  schema  required  –  Drop  it  in.  10,000+  exis-ng  applica-ons  

already  “speak  Couchbase”  (via  memcached)  –  Prac-cally  every  language  and  applica-on  

framework  is  supported,  out  of  the  box  

•  Easy  to  manage  –  One-­‐click  failover  and  cluster  rebalancing  –  Graphical  and  programma-c  interfaces  –  Configurable  aler-ng  

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Couchbase  Server  is  Simple,  Fast,  Elas-c  

•  Predictable  –  “Never  keep  an  applica-on  wai-ng”  –  Quasi-­‐determinis-c  latency  and  throughput  

•  Low  latency  –  Built-­‐in  Memcached  technology  –  Auto-­‐migra-on  of  hot  data  to  lowest  latency  

storage  technology  (RAM,  SSD,  Disk)  –  Selectable  write  behavior  –  asynchronous,  

synchronous  (on  replica-on,  persistence)  

•  High  throughput  –  Mul--­‐threaded  –  Low  lock  conten-on  –  Asynchronous  wherever  possible  –  Automa-c  write  de-­‐duplica-on  

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Couchbase  Server  is  Simple,  Fast,  Elas-c  

•  Zero-­‐down-me  elas-city  –  Spread  I/O  and  data  across  commodity  

servers  (or  VMs)    –  Consistent  performance  with  linear  cost  –  Dynamic  rebalancing  of  a  live  cluster  

•  All  nodes  are  created  equal  –  No  special  case  nodes  –  Clone  to  grow  

•  Extensible  –  Change  feeds  –  Real-­‐-me  map-­‐reduce  –  RESTful  interface  for  management  

Couchbase  Web  Console  

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Proven  at  Small,  and  Extra  Large  Scale  

•  Leading cloud service (PAAS) provider

•  Over 150,000 hosted applications •  Couchbase Server serving over

6,200 Heroku customers

•  Social game leader – FarmVille, Mafia Wars, Empires and Allies, Café World, FishVille

•  Over 230 million monthly users •  Couchbase Server is the primary

database behind key Zynga properties

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Customers  and  Partners  

Customers  (par-al  lis-ng)   Partners  

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moxi  

11211   11210  

memcached  protocol  listener/sender  

Couchbase  Storage  Engine  

engine  interface  

memcapable  1.0   memcapable  2.0  

21100  –  21199  4369  8091  

hcp  RE

ST  m

anagem

ent  A

PI/W

eb  UI  

Heartbeat  

Process  m

onito

r  

Glob

al  singleton  supe

rviso

r  

Confi

gura-o

n  manager  

on  each  node  

Erlang/OTP  

Rebalance  orchestrator  

Nod

e  he

alth  m

onito

r  

one  per  cluster  

vBucket  state  and

 replica-

on  m

anager  

HTTP   distributed  erlang  erlang  port  mapper  

Data  Manager   Cluster  Manager  

Couchbase  Server  Architecture  

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moxi  

11211   11210  

memcached  protocol  listener/sender  

engine  interface  

memcapable  1.0   memcapable  2.0  

21100  –  21199  4369  8091  

hcp  RE

ST  m

anagem

ent  A

PI/W

eb  UI  

Heartbeat  

Process  m

onito

r  

Glob

al  singleton  supe

rviso

r  

Confi

gura-o

n  manager  

on  each  node  

Erlang/OTP  

Rebalance  orchestrator  

Nod

e  he

alth  m

onito

r  

one  per  cluster  

vBucket  state  and

 replica-

on  m

anager  

HTTP   distributed  erlang  erlang  port  mapper  

Couchbase  Server  Architecture  

Couchbase  Storage  Engine  

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Couchbase  “write”  Data  Flow  –  applica-on  view  

User  ac-on  results  in  the  need  to  change  the  VALUE  of  KEY  

Applica-on  updates  key’s  VALUE,  performs  SET  opera-on    

Couchbase  client  hashes  KEY,  iden-fies  KEY’s  master  server  SET  request  sent  over  

network  to  master  server  

Couchbase  replicates  KEY-­‐VALUE  pair,  caches  it  in  memory  and  stores  it  to  disk  

1  

2  

3  4  

5  

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Couchbase  Data  Flow  –  under  the  hood  

Listener-­‐Sender

DiskDisk Disk

RAM*

mem

base  storage  e

ngine

SSDSSD SSD

Listener-­‐Sender

DiskDisk Disk

RAM*

mem

base  storage  e

ngine

SSDSSD SSD

SET  request  arrives  at  KEY’s  master  server  

Listener-­‐Sender  

Master  server  for  KEY   Replica  Server  2  for  KEY  Replica  Server  1  for  KEY  

2   2  

1   SET  acknowledgement  returned  to  applica-on  3  

Disk  Disk   Disk  

RAM*  

Couchb

ase  storage  en

gine

 

SSD  SSD   SSD  

2  

4  

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Elas-city  -­‐  Rebalancing  

vBucket  1  vBucket  2  vBucket  3  

vBucket  4  vBucket  5  vBucket  6  

Node  1   Node  2   Node  3  

vBucket  1  vBucket  2  

vBucket  3  vBucket  4  

vBucket  5  vBucket  6  

vBucket  7  vBucket  8  

vBucket  9  vBucket  10  

vBucket  11  vBucket  12  

Before  •  Adding  Node  3  •  Node  3  is  in  pending  state  •  Clients  talk  to  Node  1,2  only  

AOer  •  Node  3  is  balanced  •  Clients  are  reconfigured  to  talk  to  

Node  3  

During  •  Rebalancing  orchestrator  recalculates  

the  vBucket  map  (including  replicas)  •  Migrate  vBuckets  to  the  new  server  •  Finalize  migra-on  

vBucket  7  vBucket  8  vBucket  9  

vBucket  10  vBucket  11  vBucket  12  

Pending  state  

vBucket  1  vBucket  2  vBucket  3  

vBucket  4  vBucket  5  vBucket  6  

vBucket  7  vBucket  8  vBucket  9  

vBucket  10  vBucket  11  vBucket  12  

Rebalancing  

vBucket    migrator   vBucket    migrator  

Client  

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Data  buckets  are  secure  Couchbase  “slices”  

Couchbase  data  servers  

In  the  data  center  

Web  applica-on  server  

Applica-on  user  

On  the  administrator  console  

Bucket  1  

Bucket  2  

Aggregate  Cluster  Memory  and  Disk  Capacity  

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•  Support  large-­‐scale  analy-cs  on  applica-on  data  by  streaming    data  from  Couchbase  to  Hadoop  –  Real-­‐-me  integra-on  using  Flume  –  Batch  integra-on  using  Sqoop  

•  Examples  –  Various  game  sta-s-cs  (e.g.,  monthly  /  daily  /  hourly  rankings)  –  Analyze  game  pacerns  from  users  to  enhance  various  game  metrics    

Couchbase  and  Hadoop  Integra-on  

memcached  protocol  listener/sender  

engine  interface  

Couchbase  Storage  Engine  

TAP  

Flume  

Sqoop  

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•  Introduc-on  •  What  is  Couchbase  Server?  

–  Simple,  Fast,  Elas-c  –  Technology  Overview  (Architecture,  data  flow,  rebalancing)  

•  Tribal  Crossing  Inc:  Animal  Party  –  Challenges  before  Couchbase  

•  Original  Architecture  –  Why  Couchbase?  

•  Simplicity  •  Performance  •  Flexibility  

–  Deploying  Couchbase  •  New  Architecture  •  EC2  •  Data  Model  •  Accessing  data  in  Couchbase  

•  Product  Roadmap  •  Q&A  

Agenda  

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Common  steps  on  scaling  up  database:  

●  Tune  queries  (indexing,  explain  query)  

●  Denormaliza-on  

●  Cache  data  (APC  /  Memcache)  

●  Tune  MySQL  configura-on  

●  Replica-on  (read  slaves)  

 

Where  do  we  go  from  here  to  prepare  for  the  scale  of  a  successful  social  game?  

Tribal  Crossing:  Challenges  

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●  Write-­‐heavy  requests  –  Caching  does  not  help  –  MySQL  /  InnoDB  limita-on  (Percona)  

●  Need  to  scale  dras-cally  over  night  –  My  Polls  –  100  to  1m  users  over  a  weekend  

●  Small  team,  no  dedicated  sysadmin  –  Focus  on  what  we  do  best  –  making  games  

●  Keeping  cost  down  

Tribal  Crossing:  Challenges  

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●  MySQL  with  master-­‐to-­‐master  replica-on  and    sharding  

–  Complex  to  setup,  high  administra-on  cost  –  Requires  applica-on  level  changes  

●  Cassandra  –  High  write,  but  low  read  throughput  –  Live  cluster  reconfigura-on  and  rebalance  is  quite  complicated  –  Eventual  consistency  gives  too  much  burden  to  applica-on  

developers  

●  MongoDB  –  High  read/write,  but  unpredictable  latency  –  Live  cluster  rebalance  for  exis-ng  nodes  only  –  Eventual  consistency  with  slave  nodes  

Tribal  Crossing:  “Old”  Architecture  and  Op-ons  

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●  SPEED,  SPEED,  SPEED  

●  Immediate  consistency  

●  Interface  is  dead  simple  to  use  –  We  are  already  using  Memcache  

●  Low  sysadmin  overhead  

●  Schema-­‐less  data  store  

●  Used  and  Proven  by  big  guys  like  Zynga  

●  …  and  lastly,  because  Tribal  CAN  –  Bigger  firms  with  legacy  code  base  =  hard  to  adapt  –  Small  team  =  ability  to  get  on  the  cuung  edge  

Tribal  Crossing:  Why  Couchbase  Server?  

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●  But,  there  are  some  different  challenges  in    using  Couchbase  (currently  1.7)  to  handle  the  game  data:  

–  No  easy  way  to  query  data  –  No  transac-on  /  rollback  

➔  Couchbase  Server  2.0  resolves  them  by  using  CouchDB  as  the  underlying  database  engine  

●  Can  this  work  for  an  online  game?  –  Break  out  of  the  old  ORM  /  rela-onal  paradigm!  –  We  are  not  handling  bank  transac-ons  

Tribal  Crossing:  New  Challenges  With  Couchbase  

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Couchbase Cluster

Web Server

Tribal  Crossing:  Deploying  Couchbase  in  EC2  

●  Basic  produc-on  environment  setup  

●  Dev/Stage  environment  –  feel  free  to  install  Couchbase  on  your  web  server  

Apache

Couchbase Couchbase

DNS Entry

Client-side Moxi

Cluster Mgmt. Requests

…  

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Tribal  Crossing:  Deploying  Couchbase  in  EC2  

●  Amazon  Linux  AMI,    64-­‐bit,  EBS  backed  instance  

●  Setup  swap  space  ●  Install  Couchbase’s    Membase  Server  1.7  

●  Access  web  console http://<hostname>:8091

●  Start  the  new  cluster  with  a  single  node  

●  Add  the  other  nodes  to  the  cluster  and  rebalance  

 

Couchbase Cluster

Web Server

Apache

Couchbase

DNS Entry

Client-side Moxi

Cluster Mgmt. Requests

…   Couchbase

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Tribal  Crossing:  Deploying  Couchbase  in  EC2  

Moxi  figures  out  which  node  in  the  cluster  holds  data  for  a  given  key.  

●  On  each  web  server,  install  Moxi  proxy  

●  Start  Moxi  by  poin-ng  it  to  the  DNS  entry  you  created  

●  Web  apps  connect  to  Moxi  that  is  running  locally memcache->addServer(‘localhost’, 11211);

Couchbase Cluster

Web Server

Apache

Couchbase Couchbase

DNS Entry

Client-side Moxi

Cluster Mgmt. Requests

…  

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Use  case  -­‐  simple  farming  game:  

●  A  player  can  have  a  variety  of  plants  on  their  farm.  

●  A  player  can  add  or  remove  plants  from  their  farm.  

●  A  Player  can  see  what  plants  are  on  another  player's  farm.  

Tribal  Crossing:  Represen-ng  Game  Data  in  Couchbase  

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RepresenUng  Objects  

●  Simply  treat  an  object  as  an  associa-ve  array  

●  Determine  the  key  for  an  object  using  the  class  name  (or  type)  of  the  object  and  an  unique  ID  

RepresenUng  Object  Lists  

●  Denormaliza-on  

●  Save  a  comma  separated  list  or  an  array  of  object  IDs  

Tribal  Crossing:  Represen-ng  Game  Data  in  Couchbase  

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Player  Object  Key: 'Player1' Array ( [Id] => 1 [Name] => Shawn )

Tribal  Crossing:  Represen-ng  Game  Data  in  Couchbase  

Plant  Object  Key: 'Plant201' Array ( [Id] => 201 [Player_Id] => 1 [Name] => Starflower ) PlayerPlant  List  

Key: 'Player1_PlantList' Array ( [0] => 201 [1] => 202 [2] => 204 )  

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●  No  need  to  “ALTER  TABLE”  

●  Add  new  “fields”  all  objects  at  any  -me  –  Specify  default  value  for  missing  fields  –  Increased  development  speed  

●  Using  JSON  for  data  objects  though,  owing  to  the  ability  to  query  on  arbitrary  fields  in  Couchbase  2.0  

Tribal  Crossing:  Schema-­‐less  Game  Data  

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Get  all  plants  belong  to  a  given  player  Request: GET /player/1/farm $plant_ids = couchbase->get('Player1_PlantList'); $response = array(); foreach ($plant_ids as $plant_id) { $plant = couchbase->get('Plant' . $plant_id); $response[] = $plant; } echo json_encode($response);

Tribal  Crossing:  Accessing  Game  Data  in  Couchbase  

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Give  a  player  a  new  plant  // Create the new plant $new_plant = array ( 'id' => 100, 'name' => 'Mushroom' ); $couchbase->set('Plant100', $new_plant); // Update the player plant list $plant_ids = $couchbase->get('Player1_PlantList'); $plant_ids[] = $new_plant['id']; $couchbase->set('Player1_PlantList', $plant_ids);

Tribal  Crossing:  Modifying  Game  Data  in  Couchbase  

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Concurrency  issue  can  occur  when  mul-ple  requests  are  working  with  the  same  piece  of  data.  Solu-on:  ●  CAS  (check-­‐and-­‐set)  

–  Client  can  know  if  someone  else  has  modified  the  data  while  you  are  trying  to  update  

–  Implement  op-mis-c  concurrency  control  

●  Locking  (try/wait  cycle)  –  GETL  (get  with  lock  +  -meout)  

opera-ons  –  Pessimis-c  concurrency  control  

Tribal  Crossing:  Concurrency  

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●  Record  object  rela-onships  both  ways  –  Example:    Plots  and  Plants  

●  Plot  object  stores  id  of  the  plant  that  it  hosts  ●  Plant  object  stores  id  of  the  plot  that  it  grows  on  

–  Resolu-on  in  case  of  mismatch  

●  Don't  sweat  the  extra  calls  to  load  data  in  a  one-­‐to-­‐many  rela-onship  

–  Use  mul3Get  –  We  can  s-ll  cache  aggregated  results  in  a  Memcache  bucket  if  needed  

Tribal  Crossing:  Data  Rela-onship  

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Web  Server              

First  migrated  large  or  slow  performing  tables  and    frequently  updated  fields  from  MySQL  to  Couchbase  

Tribal  Crossing:  Migra-ng  to  Couchbase  Servers  

memcached  protocol  listener/sender  

engine  interface  

Couchbase  Storage  Engine  

TAP  

TAP  Client  

Apache  +  PHP  

Client-­‐side  Moxi  

Repor-ng  Applica-ons  

MySQL  

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Tribal  Crossing:  Deployment    

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Tribal  Crossing:  Deployment  

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•  Significantly  reduced  the  cost  incurred  by  scaling  up  database  servers  and  managing  them.  

•  Achieved  significant  improvements  in  various  performance  metrics  (e.g.,  read,  write,  latency,  etc.)  

•  Allowed  them  to  focus  more  on  game  development  and  op-mizing  key  metrics  

•  Plan  to  use  real-­‐-me  MapReduce,  querying,  and  indexing  abili-es  provided  by  the  upcoming  Elas-c  Couchbase  2.0  

Tribal  Crossing:  Conclusion  

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•  Introduc-on  •  What  is  Couchbase  Server?  

–  Simple,  Fast,  Elas-c  –  Technology  Overview  (Architecture,  data  flow,  rebalancing)  

•  Tribal  Crossing  Inc:  Animal  Party  –  Challenges  before  Couchbase  

•  Original  Architecture  –  Why  Couchbase?  

•  Simplicity  •  Performance  •  Flexibility  

–  Deploying  Couchbase  •  New  Architecture  •  EC2  •  Data  Model  •  Accessing  data  in  Couchbase  

•  Product  Roadmap  •  Q&A  

Agenda  

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•  Mobile  to  cloud  data  synchroniza-on  •  Cross  data  center  replica-on  

Product  Roadmap:  Couchbase    Server  2.0  

Couchbase  Single  Server  

US  West  Coast  Data  Center  

Couchbase  Server  

Couchbase  Single  Server  

US  East  Coast  Data  Center  

Couchbase  Server  

CouchSync  

CouchSync   CouchSync  

CouchSync  

…… …

…   …  

CouchSync  

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•  Replace  Sqlite-­‐based  storage  engine  with  CouchDB  •  Support  indexing  and  querying  on  values  •  Integrate  real-­‐-me  MapReduce  into  Couchbase  server  •  SDK  for  Couchbase  server  

Product  Roadmap:  Couchbase  Server  2.0  

The  world’s  leading  caching  and  clustering  technology  

The  most  reliable  and  full-­‐featured  document  database  

The  fastest,  most  complete  and  most  reliable  database  on  the  

planet  

Membase  Server  1.7   CouchDB  1.1   Couchbase  Server  2.0  

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•  Community  Edi-on  –  Open  source  build  –  Free  forum  support  

•  Enterprise  Edi-on  –  Free  for  non-­‐produc-on  use  –  Cer-fied,  QA  tested  version  of  open  source  –  Case  tracking  and  guaranteed  SLA  for  produc-on  environments  

•  Partner  in  Korea  –  N2M  Inc.  (hcp://www.n2m.co.kr)  

Couchbase  Product  Download  

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Q&A  Matt Ingenthron, Couchbase Inc.

([email protected], @ingenthr) Chiyoung Seo, Couchbase Inc.

([email protected], @chiyoungseo)