We can exploit cartesian products and indexing for == constraints. If its a nested model we have to iterate over all possible instances. The other problem is if the nested model changes the engine has no idea this has happened, which if you are not careful can lead to data integrity issues.
In the documents this is dicussed briefly:
“). Object models can often have complex relationships and hierarchies in them - for rules you will want to simplify and flatten the model where possible, and let the rule engine infer relationships (as it provides future flexibility.”
What does it mean that the rule engine can infer relationships?
Are there performance reasons for having a flat model?
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