What's the problem with document databases, really? To be honest, for 80% of the projects I've ever worked with, fixed-schema rdbms's fitted just like... a square peg in a round hole!
Heck, even for advanced analytics, I find mongo aggregates and mongo map reduce 10x more intuitive and SQL that inevitably ends up using zillions of non-portable tricks, stored procedures and god knows what. And atomicity and whatever else transactions guarantee you in theory can be easily emulated with some good db structure design tricks and app design tricks in practice.
And the smarter a RDBMS is, like Postgres, the more dangerous it becomes for maintainability: it's a zillion times easier to maintain 'logic expressed in app code' (because you have basic stuff like version control, tests and so on), than 'logic trapped in the db' (good luck explaining to a new developer how "X automagically happens because of trigger Y and stored procedure Z, so there is no app code for X that you can instantly tweak to change how it works"). This is why I at least have some respect for mysql: it's retarded enough that it forces you to put the login in the code, where it f belongs!
Really, give me a dumb document db like mongo any day! And if I want something "less dumb" there're things like arangodb and rethinkdb that can also do joins and graphs. And there're also "true graph-dbs" for index-less "joins"/traversals, like neo4j and orientdb, for when the relationships for when you actually end up doing more than 3 to 4 levels deep joins...
Imho the development of "high-end rdbms" like postgress and oracle has been a huge waste of human brainpower and all the benefits supposedly provided by these pieces of technology were actually from the clever app-level code that mostly worked around their inappropriateness...
I was not referring to document databases as a whole, just to MongoDB in particular. You can use PostgreSQL as a document database. I heard too many stories with Mongo where people were dealing with locks or broken data instead of solving their business problems.
Heck, even for advanced analytics, I find mongo aggregates and mongo map reduce 10x more intuitive and SQL that inevitably ends up using zillions of non-portable tricks, stored procedures and god knows what. And atomicity and whatever else transactions guarantee you in theory can be easily emulated with some good db structure design tricks and app design tricks in practice.
And the smarter a RDBMS is, like Postgres, the more dangerous it becomes for maintainability: it's a zillion times easier to maintain 'logic expressed in app code' (because you have basic stuff like version control, tests and so on), than 'logic trapped in the db' (good luck explaining to a new developer how "X automagically happens because of trigger Y and stored procedure Z, so there is no app code for X that you can instantly tweak to change how it works"). This is why I at least have some respect for mysql: it's retarded enough that it forces you to put the login in the code, where it f belongs!
Really, give me a dumb document db like mongo any day! And if I want something "less dumb" there're things like arangodb and rethinkdb that can also do joins and graphs. And there're also "true graph-dbs" for index-less "joins"/traversals, like neo4j and orientdb, for when the relationships for when you actually end up doing more than 3 to 4 levels deep joins...
Imho the development of "high-end rdbms" like postgress and oracle has been a huge waste of human brainpower and all the benefits supposedly provided by these pieces of technology were actually from the clever app-level code that mostly worked around their inappropriateness...