Graph Database

Graph database vs. Enterprise Knowledge Graph

Stardog is more than a graph database

What is a graph database?

In contrast to the relational system, which stores data in rows and columns, semantic graph organizes information using nodes and edges to represent entities and the relationships between those entities. A graph database is a place to store this graph data.

How does an Enterprise Knowledge Graph platform go beyond a graph database?

Graph databases were designed for data storage, whereas Stardog’s Enterprise Knowledge Graph platform is designed for data management. The incorporation of inference and virtualization, leveraged atop the power of semantic technology, means Enterprise Knowledge Graph is entering an entirely different category.

Like a graph databases, an Enterprise Knowledge Graph platform can rapidly traverse chains of edges to find relationships between remote, diverse pieces of data. Following multiple chains of edges simultaneously, they can identify a mesh of many-to-many interrelationships at multiple levels of granularity, from summary rollups to a record’s smallest details. In this way, relevant data can be retrieved through a single query. The advantages of the graph data model increase as data and queries become more complex, which they always do in the enterprise.

Unlike a plain graph database, an Enterprise Knowledge Graph platform also has deeply integrated functionality, which support knowledge representation in the graph and enable, among other things, machine understanding. For example, a simple graph database knows there is an interrelationship between a person node in database silo “A” and an organization node in database silo “B.” An Enterprise Knowledge Graph platform, by contrast, also understands the nature of that interrelationship; the edge property might be symmetric (both have credit card accounts), reflexive (the person works for/is employed by the organization), or transitive (the person made a payment to the organization).

Since an Enterprise Knowledge Graph platform can represent myriad data interrelationships, both explicit and inferred, they closely represent the real world in all its rich, inherent connectedness. As a result, enterprises can build highly sophisticated data models that accurately represent real-world operations, and users can view data from any point of interest.

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