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