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

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

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