1. NoSQL Solutions
Byeongweon Moon
tasyblue@gmail.com
2012.01.26

2. Redis, Couchbase, MongoDB, Membase

3. Memory Base Cache vs.
Database

5. NoSQL
• Collections (versus tables)
• Documents (versus rows)
• Loosely defined fields (versus
columns)
• Scale out (versus scale up)
• Denormalization (versus
normalization)

6. Data Model
• Relational
• Key-value
• Column-oriented
• Document-oriented

7. Relational

8. Key-value

9. Column-oriented

10. Document-oriented
FirstName="Jonathan",
Address="15 Wanamassa Point
Road",
K Children=[
E {Name:"Michael",Age:10},
Y {Name:"Jennifer", Age:8},
{Name:"Samantha", Age:5},
{Name:"Elena", Age:2}
]

11. Memory Base Cache
• Weak Persistence
• Weak Consistency
• Strong Performance
• Low Latency

12. Membase
• Based on Memcached
• Written by C++(Memcached),
Erlang(Membase)
• Distributed, in-memory key-value
database management system
• Optimized for storing data behind
web applications

13. Membase (cont’)
• Persistence
– Asynchronously writes data to disk after
acknowledging write to client
– Guarantees data consistency
• Replication and failover (server
failures recoverable in under 100ms)
• Scalability and performance
– Distributed object store
– Dynamic cluster resizing and rebalancing
– Guaranteed data consistency
– High sustained throughput
– Low, predictable latency

14. Redis
• In-memory, key-value data store
• Written by ANSI C, support various
client

15. Redis (cont’)
• Various Data Models
– List, Set, Sorted Set, Hash
– Support atomic operation about data types
• Persistence
– Data is held in memory but written to disk
asynchronously
• Replication
– Master-Slave replication
• Performance
– Non-blocking I/O. Single threaded
• Publish/Subscribe

16. Membase vs. Redis
Membase Redis
String Set, List, Sorted List,
Hash..
Master-Master Master-Slave
Storing, inc/dec API Various operations
includes pop, push,
extract …
Web management UI Console management
tool

17. How to use…
• Normally use …
$key = md5('SELECT * FROM rest_of_sql_statement_goes_here');
if ($memcache->get($key)) {
return $memcache->get($key);
}
else {
$result = $query_results_mangled_into_most_likely_an_array
$memcache->set($key, $result, TRUE, 86400);
return $result;
}

18. How to use … (cont’)
• Structured Data (array, struct…)
– Serialize
KEY VALUE
user:$user_id name:문병원|call:하겐다즈|…
– Normalization
KEY VALUE
user:$user_id:name 문병원
user:$user_id:call 하겐다즈

19. Application Design using
Membase
• Cache result other than SQL data!
• Use a cache hierarchy
• Update membase as your data
updates
• Race conditions and stale data
• Pre warm your cache
• Storing lists with keys
• Batch your requests with get_multi
From memcached FAQ

20. Database
• Persistence
• Reliable
• Scalable
• Distributed
• Clustered

21. MongoDB
• Document-oriented Storage
• High Write Performance
• Full index support
• Master/Slave Replication
• Support Map/Reduce
• Auto-Sharding
• Querying
• GridFS
• Written in C++

22. CouchDB
• Document-oriented Storage
• High Read Performance
• ACID Semantics
• Map/Reduce View and Indexes
• Distributed Architecture with
Replication
• REST API
• Eventual Consistency
• Written in Erlang

23. CASE STUDY

24. Twitter

25. Facebook Timeline

26. APPENDIX

28. CouchDB MongoDB MySQL
Document-Oriented (JS Document-Oriented
Data Model Relational
ON) (BSON)
string, int, doubl
string, number, boole e, boolean, date, Various Types L
Data Types
an, array, object byte array, object ink
, array, others
Large Object
Yes (attachments) Yes (GridFS) BlobZ
s (Files)
Horizontal p
artitioning CouchDB Lounge Auto-sharding Partitioning
scheme
Master-slave, m
Master-master (with d
Master-slave and r ulti-master, an
Replication eveloper supplied con
eplica sets d circular repl
flict resolution)
ication
Object(row)
One large repository Collection-based Table-based
Storage

29. Map/reduce of ja
vascript functio Dynamic; object-
Query Method ns to lazily bui based query lang Dynamic; SQL
ld an index per uage
query
Secondary Indexes Yes Yes Yes
Atomicity Single document Single document Yes - advanced
Native drivers ;
Interface REST Native drivers
REST add-on
Map/Reduce, serv
Server-side batch d
Map/Reduce er-side javascri Yes (SQL)
ata manipulation
pt
Written in Erlang C++ C++
Eventually consi Strong consisten Strong consiste
stent (master-ma cy. Eventually ncy. Eventuall
Distributed Consist ster replication consistent reads y consistent re
ency Model with versioning from secondaries ads from second
and version reco are available. aries are avail
nciliation) able.

30. References
• NoSQL solutions: Membase, Redis, CouchDB and MongoDB :
http://blog.fedecarg.com/2011/01/25/nosql-solutions-membase-redis-
couchdb-and-mongodb/
• Visual Guide to NoSQL Systems : http://blog.nahurst.com/visual-guide-to-
nosql-systems
• MongoDB, CouchDB, MySQL Compare Grid :
http://www.mongodb.org/display/DOCS/MongoDB,+CouchDB,+MySQL+Compare+Grid
• SQL to Mongo Mapping Chart :
http://www.mongodb.org/display/DOCS/SQL+to+Mongo+Mapping+Chart
• Memcached FAQ :
http://code.google.com/p/memcached/wiki/FAQ#Simple_query_result_caching
• Couchbase 2.0 Manual : http://docs.couchbase.org/couchbase-manual-2.0.pdf
• Building Timeline : Facebook http://www.facebook.com/notes/facebook-
engineering/building-timeline-scaling-up-to-hold-your-life-
story/10150468255628920