[docs] FAQ entry 'Does Superset work with [database engine]?'

docs/faq.rst

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+
+Does Superset work with [insert database engine here]?
+------------------------------------------------------
+
+The community over time has curated a list of databases that work well with
+Superset in the :ref:`ref_database_deps` section of the docs. Database
+engines not listed in this page may work too. We rely on the
+community to contribute to this knowledge base.
+
+.. _SQLAlchemy dialect: http://docs.sqlalchemy.org/en/latest/dialects/
+.. _DBAPI driver: https://www.python.org/dev/peps/pep-0249/
+
+For a database engine to be supported in Superset through the
+SQLAlchemy connector, it requires having a Python compliant
+`SQLAlchemy dialect`_ as well as a
+`DBAPI driver`_ defined.
+Database that have limited SQL support may
+work as well. For instance it's possible to connect
+to Druid through the SQLAlchemy connector even though Druid does not support
+joins and subqueries. Another key element for a database to be supported is through
+the Superset `Database Engine Specification
+<https://github.com/apache/incubator-superset/blob/master/superset/db_engine_specs.py>`_
+interface. This interface allows for defining database-specific configurations
+and logic
+that go beyond the SQLAlchemy and DBAPI scope. This includes features like:
+
+
+* date-related SQL function that allow Superset to fetch different
+  time granularities when running time-series queries
+* whether the engine supports subqueries. If false, Superset may run 2-phase
+  queries to compensate for the limitation
+* methods around processing logs and inferring the percentage of completion
+  of a query
+* technicalities as to how to handle cursors and connections if the driver
+  is not standard DBAPI
+* more, read the code for more details
+
+Beyond the SQLAlchemy connector, it's also possible, though much more
+involved, to extend Superset and write
+your own connector. The only example of this at the moment is the Druid
+connector, which is getting super seeded by Druid's growing SQL support and
+the recent availability of a DBAPI and SQLAlchemy driver. If the database
+you are considering integrating has any kind of of SQL support, it's probably
+preferable to go the SQLAlchemy route. Note that for a native connector to
+be possible the database needs to have support for running OLAP-type queries
+and should be able to things that are typical in basic SQL:
+
+- aggregate data
+- apply filters (==, !=, >, <, >=, <=, IN, ...)
+- apply HAVING-type filters
+- be schema-aware, expose columns and types
+