The Graph

Graphs are everywhere.

At their core, unsurprisingly, graph technologies are built on the concept of a graph. Graphs are composed of two elements: nodes and edges.

- Each node represents an entity. 
- Nodes/entities have properties and store objects. 
- Nodes are connected by links; edges. 
- Edges represent the relationship between two nodes.

Considering that highly connected data is increasing across industries at a rapid rate, it makes sense to consider them from the perspective of Corda data models. We are already seeing cordapp data models that exhibit high levels of connectedness.

Graph Query Language

GraphQL needs little introduction. GraphQL is a query language and runtime for APIs. GraphQL is a way for clients to efficiently obtain data from servers. GraphQL provides a complete and understandable description of the data in your API. It gives clients the power to ask for exactly what they need and nothing more. It makes it easier to evolve APIs over time and enables powerful developer tools. - Offical GraphQL

Graph databases

Although databases based on graphs seem complex, they are intuitive and easy to understand.

In a graph database system, relationships are stored alongside data, which means graph databases are much more performant when querying highly connected datasets. Graph databases also help to uncover insights about complex relationships within large datasets. They’re particularly good at finding unapparent or indirect relationships between distantly connected data points. Graphs, above an RDMS, give≤ the ability to explicitly and easily connect any pieces of data together without the complexity of defining and managing foreign keys and pivot tables.