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What is the difference between a Graph Database (e.g. Neo4J) and a Network Database (e.g. IDS, CODASYL)? In principle are they the same thing?
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A database organized according to ownership of records, allowing records to have multiple owners and thus providing multiple access paths to the data. Database management systems (DBMSs) providing such capabilities are also known as CODASYL (Conference on Data Systems Languages) DBMSs.
Native graph storage Unlike relational databases, Neo4j stores interconnected network data that is neither purely linear nor hierarchical.
The most notable difference between the two is that graph databases store the relationships between data as data. Relational databases infer a focus on relationships between data but in a different way. The relational focus is between the columns of data tables, not data points.
How Does a Graph Database Differ from a Relational Database? The main difference is the way relationships between entities are stored. In a graph database, relationships are stored at the individual record level, while a relational database uses predefined structures, a.k.a. table definitions.
The network databases like CODSASYL are still more or less based on a hierarchical data model, thinking in terms of parent-child (or owner-member in CODASYL terminology) relationships. This also means that in network database you can't relate arbitrary records to each other, which makes it hard to work with graph-oriented datasets. For example, you may use a graph database to analyze what relationships exist between entities.
Also, network databases use fixed records with a predefined set of fields, while graph databases use the more flexible Property Graph Model, allowing for arbitrary key/value pairs on both nodes/vertices and relationships/edges.
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