I was thinking something a bit more specific without having to
manually generate the structs.
For example, let's say I have a JSON document that has a number
of fields in it. Some are numbers, some are strings, etc. What
I'm thinking either a) based of the JSON structure or b) based on
a schema that describes the JSON, the objects and/or indices are
defined at compile-time and done so in an optimal manner. For
example, if based on the schema we know that a field is an
enumeration, instead of a inverted index a simple associative
array that contains arrays of matching document IDs is used
instead. This way, if I search on that specific field, it can be
done in the most efficient way possible. Also, the documents
themselves would be stored more optimally.
So, no, this isn't an ORM as I'm not mapping objects to an
underlying data store. I guess what I'm thinking of is the text
search equivalent of the regular expression engine. Thinking
about it now, I should have mentioned that this would be like
Sphinx/Lucene/ElasticSearch except it would be optimized to a
specific document structure vs. more general purpose. The
optimizations would be generated at compile-time based on a
sample document structure or schema vs. coding everything
manually.
