Current there's a to_dataframe() method that returns a pandas DataFrame from a query. DataFrames don't efficiently support array and struct values, but pyarrow provides efficient support for them:

In [11]: import pyarrow as pa

In [13]: a = pa.array(
    ...:     [
    ...:         {'a': [1, 2, 3]}
    ...:     ],
    ...:     pa.struct([pa.field('a', pa.list_(pa.int64()))])
    ...: )

In [14]: a
Out[14]: 
<pyarrow.lib.StructArray object at 0x7f55f8764b88>
[
  {'a': [1, 2, 3]}
]

A to_arrow() method will make it easier to efficiently support more complex types going forward in downstream libraries like ibis.