Low memory and fastest querying database for a Python project
I would recommend Postresql, only because it does what you want, can scale, is fast, rather easy to work with and stable.
It is exceptionally fast at the example queries given, and could be even faster with document querying.
I'm migrating a GAE/Java app to Python (non-GAE) due new pricing, so I'm getting a little server and I would like to find a database that fits the following requirements:

Low memory usage (or to be tuneable or predictible)
Fastest querying capability for simple document/tree-like data identified by key (I don't care about performance on writing and I assume it will have indexes)
Bindings with Pypy 1.6 compatibility (or Python 2.7 at least)

My data goes something like this:

Id: short key string
Title
Creators: an array of another data structure which has an id - used as key -, a name, a site address, etc.
Tags: array of tags. Each of them can has multiple parent tags, a name, an id too, etc.
License: a data structure which describes its license (CC, GPL, ... you say it) with name, associated URL, etc.
Addition time: when it was add in our site.
Translations: pointers to other entries that are translations of one creation.

My queries are very simple. Usual cases are:

Filter by tag ordered by addition time.
Select a few (pagination) ordered by addition time.
(Maybe, not done already) filter by creator.
(Not done but planned) some autocomplete features in forms, so I'm going to need search if some fields contains a substring ('LIKE' queries).

The data volume is not big. Right now I have about 50MB of data but I'm planning to have a huge dataset around 10GB.
Also, I want to rebuild this from scratch, so I'm open to any option. What database do you think can meet my requirements?
Edit: I want to do some benchmarks around different options and share the results. I have selected, so far, MongoDB, PostgreSQL, MySQL, Drizzle, Riak and Kyoto Cabinet.