ORM with Graph-Databases like Neo4j in Python

Question

i wonder wether there is a solution (or a need for) an ORM with Graph-Database (f.e. Neo4j). I'm tracking relationships (A is related to B which is related to A via C etc., thus constructing a large graph) of entities (including additional attributes for those entities) and need to store them in a DB, and i think a graph database would fit this task perfectly.

Now, with sql-like DBs, i use sqlalchemyś ORM to store my objects, especially because of the fact that i can retrieve objects from the db and work with them in a pythonic style (use their methods etc.).

Is there any object-mapping solution for Neo4j or other Graph-DB, so that i can store and retrieve python objects into and from the Graph-DB and work with them easily?

Or would you write some functions or adapters like in the python sqlite documentation (http://docs.python.org/library/sqlite3.html#letting-your-object-adapt-itself) to retrieve and store objects?

Answer 1

There are a couple choices in Python out there right now, based on databases' REST interfaces.

As I mentioned in the link @Peter provided, we're working on neo4django, which updates the old Neo4j/Django integration. It's a good choice if you need complex queries and want an ORM that will manage node indexing as well- or if you're already using Django. It works very similarly to the native Django ORM. Find it on PyPi or GitHub.

There's also a more general solution called Bulbflow that is supposed to work with any graph database supported by Blueprints. I haven't used it, but from what I've seen it focuses on domain modeling - Bulbflow already has working relationship models, for example, which we're still working on- but doesn't much support complex querying (as we do with Django querysets + index use). It also lets you work a bit closer to the graph.

Answer 2

Shameless plug... there is also my own ORM which you may also want to checkout: https://github.com/robinedwards/neomodel

It's built on top of py2neo, using cypher and rest API calls under hood, i.e no dependency on gremlin.

Answer 3

Maybe you could take a look on Bulbflow, that allows to create models in Django, Flask or Pyramid. However, it works over a REST client instead of the python-binding provided by Neo4j, so perhaps it's not as fast as the native binding is.