Many-to-many relationships are what gives advantage to Relational Database ModelRelational Database Model
Relational [[Database Model]] is an approach to structuring and managing data in [[Database]]s.
Data is stored in tables (also called relations) with predefined schemas (columns with specific data... over Document Database ModelDocument Database Model
Document [[Database Model]] is an approach to structuring and managing data in [[Database]]s.
Data is stored as documents (usually JSON or BSON) inside collections. Documents can be self-contained..., but in cases when we have a lot of complex many-to-many relationships, it is good to start thinking about how to model our data as a graph.
Graphs are good for evolvability: as you add features to your application, a graph can easily be extended to accommodate changes in your application’s data structures.
There are several similar ways of structuring and querying data in graphs, like Property Graph Model and Triple-Store Model.
Property Graph Model
implemented by Neo4j, Titan, InfiniteGraph…
You can think of a graph store as consisting of two relational tables, one for vertices and one for edges.
Each vertex is given a symbolic name like USA or Idaho. Other parts of the query can use those names to create edges between the vertices, using an arrow notation: (Idaho) -[: WITHIN]- > (USA) creates an edge labeled WITHIN, with Idaho as the tail node and USA as the head node.
Triple-Store Model
implemented by Datomic, AllegroGraph…
The triple-store model is mostly equivalent to the property graph model, using different words to describe the same ideas - the data is stored as triplets containing subject, predicate and object.
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