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open-source, high-performance,
schema-free, document-oriented
           database
RDBMS

• Great for many applications
• Shortcomings
 • Scalability
 • Flexibility
CAP Theorem

• Consistency
• Availability
• Tolerance to network Partitions
• Pick two

       http://www.cs.berkeley.edu/~brewer/cs262b-2004/PODC-keynote.pdf
ACID vs BASE

•   Atomicity
                  •   Basically Available
•   Consistency
                  •   Soft state
•   Isolation
                  •   Eventually consistent
•   Durability
Schema-free

• Loosening constraints - added flexibility
• Dynamically typed languages
• Migrations
BigTable

• Single master node
• Row / Column hybrid
• Versioned
BigTable

• Open-source clones:
 • HBase
 • Hypertable
Dynamo
• Simple Key/Value store
• No master node
 • Write to any (many) nodes
 • Read from one or more nodes (balance
    speed vs. consistency)
• Read repair
Dynamo

• Open-source clones
 • Project Voldemort
 • Cassandra - data model more like
    BigTable
 • Dynomite
memcached

• Used as a caching layer
• Essentially a key/value store
• RAM only - fast
• Does away with ACID
Redis

• Like memcached
• Different
 • Values can be strings, lists, sets
 • Non-volatile
Tokyo Cabinet + Tyrant

• Key/value store with focus on speed
• Some more advanced queries
 • Sorting, range or prefix matching
• Multiple storage engines
 • Hash, B-Tree, Fixed length and Table
• A lot in common with MongoDB:
 • Document-oriented
 • Schema-free
 • JSON-style documents
• Differences
 • MVCC based
 • Replication as path to scalability
 • Query through predefined views
 • ACID
 • REST
• Focus on performance
• Rich dynamic queries
• Secondary indexes
• Replication / failover
• Auto-sharding
• Many platforms / languages supported
Good at

• The web
• Caching
• High volume / low value
• Scalability
Less good at

• Highly transactional
• Ad-hoc business intelligence
• Problems that require SQL
Mongo PHP Driver

• PHP extension
• Available on PECL
          pecl install mongo
Document

• Unit of storage (think row)
• Just an Array
• Can store dates, integers, floating point,
  strings, etc.
Collection

• Schema-free equivalent of a table
• Logical groups of documents
• Indexes are per-collection
Blog back-end
Post

array(‘author’ => ‘mike’,
 ‘date’ => new MongoDate(),
 ‘text’ => ‘my blog post...’,
 ‘tags’ => array(‘mongodb’, ‘php’))
New post

$doc = array(‘author’ => ‘mike’,
 ‘date’ => new MongoDate(),
 ‘text’ => ‘my blog post...’,
 ‘tags’ => array(‘mongodb’, ‘php’));

$collection->save($doc);
Last 10 posts
$cursor = $posts->find()->
          sort(array(‘date’=>-1))->
          limit(10);

foreach($cursor as $post) {
    echo $post[‘text’];
}
Posts by author


$posts->find(array(‘author’=>‘mike’))
Posts ending with ‘PHP’


$posts->find(array(‘text’=>new MongoRegex(‘/PHP$/’)))
Posts with a tag
$posts->find(array(‘tag’=>‘mongodb’))




           ... and fast
$posts->ensureIndex(array(‘tag’=>1))
Counting posts


$posts->count()

$posts->find(array(‘author’=>‘mike’))->count()
Migration: adding titles


• Easy - just start adding them to documents
Advanced queries

    • $gt, $lt, $gte, $lte, $ne, $all, $in, $nin
    • $where clause
“this.author == ‘mike’ || this.comments.length > 5”

    • group
Other cool stuff
• Capped collections
• Unique indexes
• Mongo shell
• GridFS
• morph - http://code.google.com/p/
  mongodb-morph/
• Download MongoDB
  http://www.mongodb.org

• Install the PHP Driver
• Try it out!
• http://www.mongodb.org
• irc.freenode.net#mongodb
• mongodb-user on google groups
• @mongodb, @mdirolf
• mike@10gen.com
• http://www.slideshare.net/mdirolf

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MongoDB London PHP