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NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
NOSQL Session GlueCon May 2010
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NOSQL Session GlueCon May 2010

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Overview of NoSQL at GlueCon. Talk given by Dwight from 10gen/MongoDB.

Overview of NoSQL at GlueCon. Talk given by Dwight from 10gen/MongoDB.

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  • 1. NoSQL : Channeling the Data Explosion
    Dwight MerrimanCEO, 10gen
    @dmerr dmerr.tumblr.com
    GlueCon 2010
  • 2. The database world is changingNo longer one-size-fits-all
  • 3. NoSQL =
    Non-relational next generation operation data stores and databases
  • 4. Scaling Out
    no joins +
    light transactional semantics =
    horizontally scalable architectures
  • 5. Why?
    cloud
    commodity
    http://www.globalnerdy.com/2007/09/07/multicore-musings/
  • 6. How the NoSQL Products Vary
    What’s the same
    No joins
    No complex transactions
    What varies
    Scale-out model
    Consistency model
    Data model
  • 7. Scaling Out
    distribution & query models
    Consistent hashing
    Order preserving range
    chunking
    Scatter gather
  • 8. Data models
    no joins +
    light transactional semantics =
    horizontally scalable architectures
    Important side effect :
    new data models =
    improved ways to develop apps
  • 9. Data Models
    Key/value
    Column-oriented “bigtable-style”
    Document-oriented (JSON)
  • 10. Data Models
    { title: ‘Too Big to Fail’,
    author: ‘John S’,
    ts: Date(“05-Nov-09 10:33”),
    comments: [ { author: 'Ian White',
    comment: 'Great article!' },
    { author: 'Joe Smith',
    comment: 'But how fast is it?',
    replies: [ {author: 'Jane Smith',
    comment: 'scalable?'} ]
    }
    ]
    ],
    tags: [‘finance’, ‘economy’]
    }
  • 11. { title: ‘Too Big to Fail’,
    author: ‘John S’,
    ts: Date(“05-Nov-09 10:33”),
    comments: [ { author: 'Ian White',
    comment: 'Great article!' },
    { author: 'Joe Smith',
    comment: 'But how fast is it?',
    replies: [ {author: 'Jane Smith',
    comment: 'scalable?'} ]
    }
    ]
    ],
    tags: [‘finance’, ‘economy’]
    }
    db.posts.find( { tags : ‘economy’ } )
    .sort({ts:-1}).limit(10).skip(10)
    db.posts.find( { “comments.author” : “Ian White” } )
  • 12. Influences
  • 13. CAP
    It is impossible in the asynchronous network model to implement a read/write data object that guarantees the following properties:• Availability• Atomic consistency in all fair executions (including those in which messages are lost).
  • 14. Consistency Models - CAP
    Choices are AP or CP
    Write Availability, not Read Availability, is the Main Question
    It’s not all about CAP
    Eventual consistency makes these non-availability aspects better:
    Multi data center
    Speed
    Even load distribution
  • 15. Eventual Consistency
  • 16. Eventual Consistency
    Read(x) : 1, 2, 2, 4, 4, 4, 4 …
  • 17. Could we get this?
    Read(x) : 1, 2, 1, 4, 2, 4, 4, 4 …
  • 18. Terms
    R
    W
    N
    R+W>N has nice properties
    Sloppy quorum
  • 19. R+W>N
    If R+W > N, we can’t have both fast local reads and writes at the same time if all the data centers are equal peers?
  • 20. Network Partitions
  • 21. Trivial Network Partitions
  • 22.
  • 23. Sometimes we need global state / more consistency
    Unique key constraints
    User registration
    ACL changes
    Are we surprising the user?
    read-your-own-writes
  • 24. Could it be the case that…
    uptime( CP + average developer )
    >=
    uptime( AP + average developer )
    where uptime:= system is up and non-buggy?
  • 25. Predictions
    JSON will be the most popular building block for non-relational data models
    Tunable consistency in all the products
    Some SQL in these products!
  • 26. Questions?Thank you
    dwight@10gen.com
    @dmerr
    dmerr.tumblr.com
    @mongodb
    Download : www.mongodb.org
    10gen is hiring in SF and NYC – info@10gen.com

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