Graph Database Overview

Changes in database technology

Changes in database technology from a historical perspective that show how graph thinking emerged.

  • 1960s: hierarchical
  • 1980s: relational
  • 2000s: NoSQL
  • 2020s: graph thinking

Introduction to graph databases

Graph data is based on mathematical graph theory. It consists of points (Node/Vertex) that represent data for individual objects, groups (Label) of objects with similar characteristics, and lines (Edge) that represent relationships between objects.

graph-database
The concept of a graph that shows human relationships with points and lines

Graph theory terms

Let’s look at terms used in graph theory.

Types of graphs

Term Description
Graph A data structure that organizes relationships between things as Nodes and Edges
Directed Graph A graph whose Edges between Nodes have direction
Undirected Graph A graph whose Edges between Nodes have no direction, where the relationship between two Nodes is bidirectional
Weighted Graph A graph whose Edges between Nodes have weights
Unweighted Graph A graph whose Edges between Nodes have no weights, where all Edges have equal strength

Resources in Graph

Term Description
Node An entity in ontology
Edge A relation in ontology
Properties Information related to Nodes and Edges
Label A Role in ontology

Properties on Node: Node properties

Term Description
title Node name
caption Node description

:Properties on Edge: Edge properties

Term Description
Directionality Connection direction
Weight Connection weight

Data collection

Term Description
Node List A list of all Nodes
Edge List A list of all Edges
Adjacency Matrix A two-dimensional table of all Nodes x all Nodes.
Each entry represents the Edge state numerically. Example: -1 means no connection, 1 to N means Weight.
Neighbors A list of Nodes adjacent to a Node

References