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open-­‐source,	
  high-­‐performance,	
  
 document-­‐oriented	
  database
Non-relational
                         Operational Stores
                                    (“NoSQL”)




New Gen. OLAP                                     RDBMS
(vertica,	
  aster,	
  greenplum)               (Oracle,	
  MySQL)
NoSQL Really Means:
 non-­‐relational,	
  next-­‐generation	
  
 operational	
  datastores	
  and	
  databases
no	
  joins
+   no	
  complex	
  transactions

Horizontally Scalable
        Architectures
no	
  joins
+   no	
  complex	
  transactions

    New Data Models
New Data Models
improved	
  ways	
  to	
  develop	
  applications?
Data Models
           Key	
  /	
  Value
      memcached,	
  Dynamo

             Tabular
              BigTable

     Document	
  Oriented
MongoDB,	
  CouchDB,	
  JSON	
  stores
• memcached
scalability	
  &	
  performance



                                      • key/value



                                                                            •   RDBMS




                                             depth	
  of	
  functionality
JSON-style Documents
           represented	
  as	
  BSON

      {“hello”:	
  “world”}

  x16x00x00x00x02hello
  x00x06x00x00x00world
  x00x00


                            http://bsonspec.org
Flexible “Schemas”

                        {“author”:	
  “eliot”,
{“author”:	
  “mike”,
                        	
  “text”:	
  “...”,
	
  “text”:	
  “...”}
                        	
  “tags”:	
  [“mongodb”]}
Dynamic Queries
Atomic Update
  Modifiers
Focus on Performance
Replication
                            master   slave

        master
                            master   slave


slave       slave   slave   master   master

                             slave   master
Auto-sharding
                   Shards
          mongod   mongod    mongod
                                            ...
Config     mongod   mongod    mongod
Servers

mongod

mongod

mongod
                   mongos    mongos   ...


                    client
Many Supported
Platforms / Languages
Best Use Cases
                                        T

Scaling	
  Out
                              Caching
                 The	
  Web

            High	
  Volume
Less Good At
     highly	
  transactional


ad-­‐hoc	
  business	
  intelligence


problems	
  that	
  require	
  SQL
A Quick Aside
_id                  special	
  key
  present	
  in	
  all	
  documents
 unique	
  across	
  a	
  Collection
           any	
  type	
  you	
  want
Post

{author:	
  “mike”,
	
  date:	
  new	
  Date(),
	
  text:	
  “my	
  blog	
  post...”,
	
  tags:	
  [“mongodb”,	
  “intro”]}
Comment

{author:	
  “eliot”,
	
  date:	
  new	
  Date(),
	
  text:	
  “great	
  post!”}
New Post
post	
  =	
  {author:	
  “mike”,
	
  	
  date:	
  new	
  Date(),
	
  	
  text:	
  “my	
  blog	
  post...”,
	
  	
  tags:	
  [“mongodb”,	
  “intro”]}

db.posts.save(post)
Embedding a Comment

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

db.posts.update({_id:	
  post._id},	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  {$push:	
  {comments:	
  c}})
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}})
Posts Ending With ‘Tech’


db.posts.find({text:	
  /Tech$/})
Posts With a Tag
db.posts.find({tags:	
  “mongodb”})


          ...and Fast
                 (multi-­‐key	
  indexes)

db.posts.ensureIndex({tags:	
  1})
Indexing / Querying
    on Embedded Docs
                            (dot	
  notation)

db.posts.ensureIndex({“comments.author”:	
  1})

db.posts.find({“comments.author”:	
  “eliot”})
Counting Posts


db.posts.count()

db.posts.find({author:	
  “mike”}).count()
Basic Paging

page	
  =	
  2
page_size	
  =	
  15

db.posts.find().limit(page_size)
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  .skip(page	
  *	
  page_size)
Migration: Adding Titles
                                        (just	
  start	
  adding	
  them)

post	
  =	
  {author:	
  “mike”,
	
  	
  	
  	
  	
  	
  	
  	
  date:	
  new	
  Date(),
	
  	
  	
  	
  	
  	
  	
  	
  text:	
  “another	
  blog	
  post...”,
	
  	
  	
  	
  	
  	
  	
  	
  tags:	
  [“mongodb”],
     	
  	
  	
  	
  	
  	
  	
  title:	
  “MongoDB	
  for	
  Fun	
  and	
  Profit”}

post_id	
  =	
  db.posts.save(post)
Advanced Queries

             $gt,	
  $lt,	
  $gte,	
  $lte,	
  $ne,	
  $all,	
  $in,	
  $nin


db.posts.find({$where:	
  “this.author	
  ==	
  ‘mike’	
  ||
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  this.title	
  ==	
  ‘foo’”})
Other Cool Stuff
aggregation	
  and	
  map/reduce
capped	
  collections
unique	
  indexes
mongo	
  shell
GridFS
geo
slides	
  will	
  be	
  up	
  on	
  http://dirolf.com




Download MongoDB
         http://www.mongodb.org




   and	
  let	
  us	
  know	
  what	
  you	
  think
       @mdirolf	
  	
  	
  	
  @mongodb
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