Best way to implement these CRUD-(like) operations

Why would you need to iterate for CRUD operations? I thought a dictionary the keyed lookup was faster than iterating through an array (there may be a case where small arrays are faster, but you'd have to perf analyse that).

The .NET dictionary allows access to the Keys and values as separate lists should you need them. 

Of course the real solution is to create a generic interface to your system and perf test with different data structures   Borland's BIDS library was a great example where the underlying data structure (array, linked list, doubly linked list) was changeable for each algorithmic data type (queue, stack, etc), allowing you to test the performace of different implementations.

Herbie

EDIT:  Additionally, you might want to look up how relational databases handle these types of things:  probably a balanced tree implementation would be a good place to start for fast searches.

Right, OK, so not really your basic CRUD then.

The way I think of  balanced tree is that it's optimised to compartmentalise data through one dimension, but you need to comparmentionalise data through N-dimensions.  So you need a way to group the data into blocks where each block represents a partition of the n-dimensional space, but in such a way that you can quickly tell if a specific point is greater than or less than each of the n-dimension partitions of that block so you can 'zoom in' to the correct place easily.

Yeah. Good luck with that  

So are you looking for a specific piece of data with a specific co-ordinate (like you know specifically that there is a piece of data for [1, 2, 3]?  If so, could you create a hash for the specific co-ordinate and use a hashtable for storage and retrieval.

Or are you more like looking for all the data within a bounded range\area?  That's not going to be easy.

Let us know how you get on.

Herbie