I'm trying to wrap my head around how to structure some data. And then execute queries that return a subset of the data (which, obviously, matches some criteria.)
For example, say I am a utility company that manages sewer and cable lines. I have a DB of 500K homes, 2000K other residencies, substations, etc. I also have connections going from home to home, home to buildings, ...to substations, etc... Now, I need to be able to find all occurrences in the DB where 4 homes are in a (near) exact spatial relationship to each other (indicating one type of connection cable was probably used) and within a certain distance another (but different) exact configuration of things exists. Ideally, I would to be able to cover as much as possible of the space with these various "Cookie-cutter" patterns. Does that use-case make sense? I have ways of brute forcing such things in SQL, but it is ugly. It seems like Graph DBs would be a much better fit: distances can easily be a property on an edge, KD tree and other data structures could coexist with other structures, explorattory models could be spun up and down as needed... If anyone could point me in the right direction I would really appreciate it. Thanks Chris Moses -- You received this message because you are subscribed to the Google Groups "Neo4j" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
