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Interesting observation, @gibsonf1. What kind of hierarchical queries do you have in mind that would be challenging to write in SQL? Would you mind sharing them in natural language?

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Our conceptual awareness AI uses recursive conceptual inference where given some entity, looking at its states, the system determines which concepts can be inferred directly from those states, then precedes to then also infer that that entity inherits all the properties of the genera concepts of those starting conceptual types. If you follow the recursion, it can be quite a large number of jumps, but incredibly fast.

For our data, we use Apache Solr, but a schema modeled on how we think the human schema works - its quite simple actually.

Documentation databases operate in tree structures

- MongoDB

- ZODB

- Others

- This is also how disk file systems operate

You access items by their path, instead of id. Also path is relevant how the data is physically stored, fetching nearby data being cheaper.

To work with this kind of data in SQL you need to construct recursive CTE queries. While it’s possible, it is a bit akward sometimes.

jsonb queries in postgres have been very performant for us over +tb data sets. however, we often materialize views of large json blobs, just cause we can.

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