Notice I didn't just say it was elegant, I said why: "There are no tables to mess with and no joins (everything is explicitly joined)."

I find elegance in simplicity. If you don't need the tabular features of a relational database, why not use a graph DB for relational data? It's like a key value store with directly connected relationships.

This is so much simpler than having to deal with creating tables, DDLs, and migrations:

  >>> g = Graph()
  >>> james = g.vertices.create(name="James")
  >>> julie = g.vertices.create(name="Julie")
  >>> g.edges.create(james, "knows", julie)

Futhermore, there's no impedance mismatch so your code is cleaner.

But regardless, this is Hacker News where people explore, build, and share new things. I hope we're not moving to a place where that gets admonished.

I've actually looked a bit at bulbflow before, being a Python programmer who has had an interest in graph databases for quite some time. That's why I asked my question originally. Can you give an example of the types of relations you're using the DB to represent in a blog?

These are the base elements:

  * Nodes/Vertices: Person, Topic, Entry
  * Relationships/Edges: Tagged, Authored

  person -- authored --> entry
  entry -- tagged --> topic

Here's the base model: https://github.com/espeed/lightbulb/blob/master/lightbulb/mo...

The comment system is a separate, generic component.

Marko, the guy who created Gremlin (https://github.com/tinkerpop/gremlin/wiki), just released a Gremlin Tree step (https://github.com/tinkerpop/gremlin/wiki/Tree-Pattern), which makes it really easy to build a threaded comment tree in one quick shot.

If you have a large blog or content system, you can use likes and views to make content recommendations using a basic Gremlin collaborative filtering query:

  // calculate basic collaborative filtering for vertex with user_id
  def rank_items(user_id) {
      m = [:]
      g.v(user_id).out('likes').in('likes').out('likes').groupCount(m)
      m.sort{a,b -> a.value <=> b.value}
      return m.values()
  }

If you use Facebook, Twitter, or GitHub to authenticate users you can easily incorporate friends and followers into the recommendations.

Thanks for taking the time to explain, I'll definitely be doing some reading over the code.

I was really responding to mgkimsal, who brought up elegance. I'm all for experimentation, I am not for technical debates short on technical content. Please continue.