The graph database technology

New ideas need new technologies!

The alignment of on large structures with ADs beyond 100.000 accounts prompted us already in the design of to think about alternatives to traditional databases. Our goal was to be able to offer analytics even in "big data" environments in an exceptionally short time.

That's why we chose the graph-oriented database of neo4j .

Contrary to the known way of storing data in tables with relations, the data in a graph database are filed completely naturally. For example, each account, group, directory, or ACE corresponds to a node, which is then connected to the corresponding nodes via an "edge" (technical term for relation in graph theory). The key advantage lies in the access to the data. While in relational databases you have to query the linked objects via joins, in a graph database you can simply follow the corresponding traversal with a match command. Querying deep nesting in a relational database is very expensive. Here the graph can show its strength.

Out of thisApproach There are unique possibilities for the analysis of authorization questions in the file server environment. As tests have proven, the Query permissions even in ADs with more than 100.000 users and groups then no challenge!

Here is an example of the structure of a graph-oriented database:

In contrast, the filing in a relational construct:

And finally an (exemplary) presentation of the database of migRaven: