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> I can create domain models that almost every SQL database would struggle with that MongoDB could breeze through and vice versa.

I am always interested in learning about models that SQL/"traditional relation model" can't easily (or less easily) represent or query. Last time I asked someone pointed me to Datomic's EAVT (entity-attribute-value-time) model as a good example.

Do you know of any more than EAVT?

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One classic example is tree/graph structured data.

I've worked extensively with modeling and querying medical concepts and relationships in RDBMS. I realize there are tools like recursive common table expressions an materialized paths that can aide querying such data, but now that I'm working at a different job using neo4j, I can see how much simpler the medical informatics domain could be modeled and traversed in a graph database.

There's also all the models that requires a lot of partitioning because there will be a lot of data or of simultaneous queries. A relational database is only relational on a single server. Partitioning breaks the relationships (like, no joins between tables that exist on different servers). The new generation of SQL databases like VoltDB and Google F1 target this case, I don't know at which price.

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