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NoSQL : Various Shapes and Sizes• Document Databases• Column-family Oriented Stores• Key/value Data stores• XML Databases• Object Databases• Graph Databases
Key Questions• How do I model data for my application?• How do I determine which one is right for me?• Can I easily shift from one database to the other?• Is there a standard way of storing, accessing, and querying data?
Agenda for this session• Explore some of the main NoSQL products• Understand how they are similar and different• How best to use these products in the stack•
RWN Math• R – Number of nodes that are read from.• W – Number of nodes that are written to.• N – Total number of nodes in the cluster.• In general: R < N and W < N for higher availability
R+W>N• Easy to determine consistent state• R + W = 2N • absolutely consistent, can provide ACID gaurantee• In all cases when R + W > N there is some overlap between read and write nodes.
R = 1, W = N• more reads than writes•W=N • 1 node failure = entire system unavailable
R = N, W =1•W=N • Chance of data inconsistency quite high•R=N • Read only possible when all nodes in the cluster are available
R = W = ceiling ((N + 1)/2)Effective quorum for eventual consistency
Eventual consistency variants• Causal consistency -- A writes and informs B then B always sees updated value• Read-your-writes-consistency -- A writes a new value and never see the old one• Session consistency -- read-your-writes-consistency within a client session• Monotonic read consistency -- once seen a new value, never return previous value• Monotonic write consistency -- serialize writes by the same process
Dynamo Techniques• Consistent Hashing (Incremental scalability)• Vector clocks (high availability for writes)• Sloppy quorum and hinted handoff (recover from temporary failure)• Gossip based membership protocol (periodic, pair wise, inter-process interactions, low reliability, random peer selection)• Anti-entropy using Merkle trees• (source: http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon- dynamo-sosp2007.pdf)