DOCDB is a minimalist approach to a document oriented database using REDIS as backend.
It works more to show NoSQL patterns than for real life use.
Most of this are musings about information retrieval techniques over a document database...
There is a small prototype of a HTTP based document db in python and a script to help understand the variation and distribution of words in distinct books.
Look in books/ folder to download the example books, and run doc_to_sets.py passing them as arguments. 
The number of sets dont grow too much after the 4 books, and it tends to stop growing after a lot of data was fed.

The same idea is applied on docdb:

Assume a document DOC, which has N words. A HTTP POST to docdb would work as:

_id = INCR NEXT.DOC
SET DOCID:_id DOC
SET DOCMETA:_id DOC's metadata (name, tstamp, revision)
acc=0
for i in DOC.split():
        if i in stopwords: 
                break
        word = stem(i)
        SET ADD set_word _id
        acc++

{_id, acc}

and yield the following response:

{_id:1, wordcount:""}

Generate a unique ID for DOC.
For each word in DOC that isn't a stop word, get its stem and add the generated id to a SET with it.


To find documents containing a list of words, the search would be the intersection of all ids found inside these SETs

find([a, b, c]):
        return intersect(set_a, set_b, set_c)


Future ideas:
Revisions could be achieved with lists
LSET DOCREV:_id with latest revision 
They could be diffs agains the original version, or a namespace could be introduced to group them (as in a SET):
SET_DOC_VERSIONS:_id