Some graph database vendors propagandize index-free adjacency for the implementation of graph models. There has been some discussion on Wikipedia about what makes a database a graph database. These vendors tried to push the definition of index-free adjacency as foundation of graph databases, but were stopped by the community.

Max published an article on O’Reilly Radar about the use case he presented on Strata+Hadoop World in London earlier this year.

Max wrote an inspiring article about graphs in data modeling on Medium, packed with his own thoughts – “to sort out some things in my brain” (Max).

He asks and answers the question: Are graphs and graph databases useful in data modeling, and if so, for what and under which circumstances?

In his article, he goes all the way down from the theoretical approach of what is a graph? towards storing a graph in different storage models (RDBMS, document store and graph databases) to querying a graph and finally to his personal conclusion.

After defining a graph and filling it with some vertices and edges (see part 1), the time has come to retrieve information out of the graph.

Please take a look at the defined graph operations of ArangoDB. These will be the base for our next examples. (Yes, there may be other ways to get the results, this post does not claim completeness!)

We will start with some easy stuff and then smoothly advance in complexity.

Question: “How many edges are defined within the graph?”

Answer:

First we have to define an AQL-query:

String query = "for i in GRAPH_EDGES('Academical', null) return i";

In our..

With ArangoDB 2.2 the new graph API was released featuring multi collection graphs (see blog). With the new version (2.2.1) of arangodb-java-driver the new graph API is supported. In the following you can find a small example of creating a graph with Java.

For the import via maven and configuring the driver, please read the Basics and Driver Setup. For the following we assume, that arangodbDriver is a configured instance of the driver.

So let’s start the whole thing…

In the database we need a graph containing collections for the vertices and edges (defined in edge definitions).

MongoDB is a document DB whereas ArangoDB is a multi-model DB supporting documents, graphs and key/values within a single database. When it comes to data modeling and data querying, they pursue somewhat different approaches.

In a Nutshell: In MongoDB, data modeling is “aggregate-oriented”, avoiding relations and joins. On the other side, everybody has probably used relational databases which organize the data in tables with relations and try to avoid as much redundancy as possible. Both approaches have their pros and cons. ArangoDB is somewhat in-between: You can both model and query your..