What order of scale are you hoping for?

Mechanisms that will work well for say 4 to 16 nodes will often fail hopelessly if you try to scale them to 100 or 1000 nodes. Conversely, algorithms that will scale to 1000 nodes will usually be relatively inefficient if used for only 4 or 8 nodes.

A conflict resolution algorithm in case two different clients updated an object at the same time without seeing what the other was doing.

In general, it is far better to avoid this possibility than to design algorithms to handle it. Synchronisation always imposes high overheads on all operations. Even read(only) ones.

The best approach to distributed data management--assuming your application can be made to fit--is to distribute your objects across the nodes, but only allow the owning node to manipulate the object. Ie. route all operations on an object to its owning node. (Or nodes for failover; but only to secondaries if the primary fails.)

A quick browse of Riak link provided shows that it does this for you at the physical data (disk) level, but you will still need to provide a similar mechanism, perhaps based upon the underlying 160-bit space, at the application logic level.

Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
"Science is about questioning the status quo. Questioning authority".
In the absence of evidence, opinion is indistinguishable from prejudice.

In reply to Re^3: Any NoSQL equivalents of an ORM? by BrowserUk
in thread Any NoSQL equivalents of an ORM? by tilly

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