I am trying to understand if I should use a GraphDB for my project. I am mapping a computer network and I use NetworkX. The relationships are physical or logical adjacency (L2 and L3) . In the current incarnation my program scans the network and dumps the adjacency info in a Postgress RDB. From there I use Python to build my graphs using NetworkX.
I am trying to understand if I should change my approach and if there is any benefit in storing the info in a GaphDB. Postgress has AgensGraph which seems to be built on top of Postgress as a GraphDB overlay or addon. I don not know yet if installing this on top will make my life easier. I barely survived the migration from SQLite to Postgress :-) and to SQLAlchemy so now in not even 3 months I am reconsidering things while I can (the migration is not complete)
I could chose to use a mix but I am not sure if it makes sense to use a GraphDB. From what I understand these has advantages as not needing a schema (which helps a lot for a DB newbie like me)
I am also wondering if NetworkX (Python librayr) and GraphDB overlap in any way. As far as I understand these things NetworkX could be instrumental in analyzing the topology of the graph while GraphDB is mainly used to query the data stored in the DB. Do they overlap in anyway? Can they be used together?
TLDR: Use Neo4j or OrientDB to store data and networkx for processing it (if you need complicated algorithms). It will be the best solution.
I strongly don't recommend you to use GraphDB for your purposes. GraphDB is based on RDF that is used for semantic web and common knowledge storage. It is not supposed to be used with problems like yours. There are many graph databases that will fit to you much better. I can recommend Neo4j (the most popular graph database, as you can see; free, but non-open-source) or OrientDB (the most popular open-source graph database).
I used graph database when I had a similar problem (but I used HP UCMDB, that is corporate software and is not free). It was really MUCH better than average relational DBs. So the idea of graph database usage is good and it fits to this kind of problems naturally.
I am not sure you really need networkx to analyze the graph (you can use graph query languages to it), but if you want, you can load the data from your DB to networkx with GraphML or some another methods (OrientDB is similar) to process it using networkx.
And the little question-answer quiz in the end:
As far as I understand these things NetworkX could be instrumental in analyzing the topology of the graph
Absolutely right.
while GraphDB is mainly used to query the data stored in the DB.
It is a database. And, yes, it is mainly used to query the data.
Do they overlap in anyway?
They are both about graphs. Of course they overlap :)
Can they be used together?
Yes, they can. No, they should not be used together for your problem.