Divan DB is my pet database. I created it to scratch an itch [Nitpickers: please note this!], to see if I can create Couch DB like system in .NET. You can read all about it in the following series of posts.

It stalled for a while, mostly because I run into the hard problems (building map/reduce views). But I think that I actually have a better idea, instead of trying to build something that would just mimic Couch DB, a .NET based Document DB is actually a very achievable goal.

The way it would work is actually pretty simple, the server would accept Json-formatted documents, like those:

[
    {
        "id": 153,
        "type": "book",
        "name": "Storm from the Shadows",
        "authors": [
            "David Weber"
        ],
        "categories": [
            "SciFi",
            "Awesome",
            "You gotta read it"
        ],
        "avg_stars": 4.5,
        "reviews": [13,5423,423,123,512]
    },
    {
        "id": 1337,
        "type": "book",
        "name": "DSLs in Boo",
        "authors": [
            "Ayende Rahien",
            "Oren Eini"
        ],
        "categories": [
            "DSL",
            ".NET",
            "You REALLY gotta read it"
        ],
        "avg_stars": 7,
        "reviews": [843,214,451]
    }
]

Querying could be done either by id, or using a query on an index. Indexes can be defined using the following syntax:

var booksByTitle = 
   from book in docs
   where book.type == "book"
   select new { book.title };

The fun part here is that this index would be translated into a Lucene index, which means that you could query the index using a query:

Query(“booksByTitle”, “title:Boo”) –> documents that match this query.

As well as apply any & all the usual Lucene tricks.

You don’t get Map/Reduce using this method, but the amount of complexity you have is quite low, and the implementation should take only several days to build.

Thoughts?