SQL: Status of the legacy mode?
To discuss: do we regard the sql legacy mode (using a DBAPI2 connection, for sqlite and mysql) as a _'first-class citizen'_ in pandas? Or is it mainly for backwards compatibility? 
Is it useful to have something that is not dependent on sqlalchemy? And consequently we alo try to enhance it /accept enhancements to it? Or is it really just 'legacy' and we don't develop it further (only bug fixes)?

I think it is important to discuss this (and 'formally' decide on this), as there are some issues with this:
- If it is mainly for backwards compatibility, are we also planning to deprecate it? (which is not necessarily the consequence, if we just regard it as what the name says: legacy)
- If it is not only for backwards compatibility, why do we raise a warning?:
  
  ```
  UserWarning: Not an SQLAlchemy engine,
  attempting to use as legacy DBAPI connection
  ```
  
  As this implies to me that it is not really preferred to use this.
- Do we want to keep the functionality equal to the sqlalchemy version? (as we are using the same functions for both, it would make it complex if it is not)
  - Eg, we could easily provide a `read_table` functionality to legacy mode, by just doing a `read_sql("SELECT * FROM specified_table", ..)`.
- We should clarify the docs on this status: http://pandas-docs.github.io/pandas-docs-travis/io.html#legacy (as it is not really clear now)
- If we decide we want to fully support this, we should maybe try to find another name than 'legacy' .. :-)

Maybe the bottom line we should ask ourselves is: do we want that we can really _recommend_ it to users to use the legacy sqlite without sqlalchemy version? (and in that case I think it should be fully supported and not regarded as 'legacy')
