open-source, high-performance, document-oriented database

Aaron Stapleaaron@10gen.co

m

Version 1.6comes out in 2 weeks

Production Examples

RDBMSRDBMS(Oracle, MySQL)(Oracle, MySQL)

New Gen. New Gen. OLAPOLAP

(vertica, aster, (vertica, aster, greenplum)greenplum)

Non-Non-relationalrelational

Operational Operational StoresStores(“NoSQL”)(“NoSQL”)

non-relational, next-generation operational datastores and databases

NoSQL Really Means:

Horizontally Scalable

Architectures

no joins

no complex transactions+

New Data Models

no joins

no complex transactions+

New Data Modelsmore natural ways to develop

applications?

JSON-style Documents

{“hello”: “world”}

\x16\x00\x00\x00\x02hello\x00\x06\x00\x00\x00world\x00\x00

http://bsonspec.org

represented as BSON

Flexible “Schemas”

{“author”: “mike”, “links”: 3, “date”: "Sun Jul 18 2010 14:40:20 GMT-0700 (PDT)" “text”: “...”}

Flexible “Schemas”

{“author”: “eliot”, “date”: "Sun Jul 18 2010 14:40:22 GMT-0700 (PDT)" “text”: “...”, “tags”: [“mongodb”]}

Dynamic Queries

Posts by Author

db.posts.find({author: “mike”})

Last 10 Posts

db.posts.find() .sort({date: -1}) .limit(10)

Posts Since April 1

april_1 = new Date(2010, 3, 1)db.posts.find({date: {$gt: april_1}})

Index any combination of fields, including embedded fields

Indexes{“author”: “mike”, “links”: 3, “date”: "Sun Jul 18 2010 14:40:20 GMT-0700 (PDT)" “text”: “...”}

db.posts.ensureIndex({links: 1})

Indexes{author: “mike”, …, comments: [ {author: “eliot”, date: new Date(), text: “great post!”} }, … ] }

db.posts.ensureIndex({‘comments.author’: 1, ‘comments.date’: -1 })

Advanced Queries and Map/Reduce

Support

Posts Ending With ‘Tech’

db.posts.find({text: /Tech$/})

Posts With a Tagdb.posts.find({tags: “mongodb”})

...and Fastdb.posts.ensureIndex({tags: 1})

(multi-key indexes)

Variety of Operators

db.posts.find( {$or: [{a:1}, {b:{$mod:[5,2]}} ]})

Map/Reduce> m = function() { emit(this.user_id, 1); }> r = function(k,vals) { return 1; }> res = db.events.mapReduce(m, r, { query : {type:'sale'} });> db[res.result].find().limit(2){ "_id" : 8321073716060 , "value" : 1 }{ "_id" : 7921232311289 , "value" : 1 }

Atomic Updates, Unique Key Constraints

Embedding a Comment

c = {author: “eliot”, date: new Date(), text: “great post!”}

db.posts.update({_id: post._id}, {$push: {comments: c}})

Many Supported Platforms / Languages

with Native Drivers

Focus on Performance

Focus on performance

depth of functionality

scala

bil

ity

& p

erf

orm

an

ce •memcached•key/

value

•RDBMS

Replication and Replica Sets

master

slave slave

master

slavemaster

slavemaster

slave

I II III

Auto Sharding

client

mongos ...mongos

mon

god

...

Shards

mongod

mongod

mongod

ConfigServers

mon

god

mon

god

mon

god

mon

god

mon

god

mon

god

mon

god

mon

god

...

Auto Shardingat bit.ly

•Sharding used for bit.ly user history

•~50M users (as of late May)

•Shard on user id

•Three secondary indexes

Features you guys care about

Geospatial Indexing

db.places.ensureIndex( { loc : "2d" } )

db.places.find( { loc : { $near :[50,50] } } ).limit(20)

Geospatial Indexingdb.places.ensureIndex(

{ location : "2d" , category : 1 } );

db.places.find( { location : { $near : [50,50] }, category : 'coffee' } );

Geospatial Indexing

•Also support matching within a spatial box

•And within a a circle

Geospatial Indexing at Foursquare

•~1.3M registered users. ~615k checkins/day. Nearly 50M checkins total (as of late May). Very rapid growth.

Geospatial Indexing at Foursquare•“Who’s here” service – tracks last

3 hours for every user – uses mongo exclusively

•All checkins, tips, venues written to mongo, reads a mix of mongo / legacy postgres (as of late May)

•Migrating geo related reads to mongo first

GridFS

•Store large files by splitting them into smaller documents

•Leverages existing sharding and replication configuration

•Store metadata along with files

•Works well behind a cdn

A Note on Security•Mongo supports basic per

database authentication

•No encryption

•Not security hardened (designed to work in a safe environment behind a firewall)

•Consider ssh tunnel from app server

Wordnik Configuration•1000 requests of various types /

second

•5 billion documents (1.2TB)

•Single 2x4 core server 32gb ram, FC SAN non virtualized

•NOTE: Virtualized storage tends to perform poorly, for example if you are on EC2 you should run several EBS volumes striped

Best Use Cases

The (Mobile) Web

High Volume• User comments, voting• Real time analytics

Scaling Out• User profile, session data• Content management

Caching• Fast, in-memory caching tier

Simplify Development• No ORM or fixed schema• Easy to install and maintain

•Commercial support

•Production support, 24x7

•Consulting

•Supercharge your app development

•Training

•Learn from the experts

•10gen.com

Download MongoDBmongodb.org

let us know what you think@mongodb

get free supportgroups.google.com/group/mongodb-user

request featuresjira.mongodb.org

(grab some friends and manipulate ourvoting system )