Graphs come in various types, each with distinct characteristics. GQL primarily focuses on property graphs. Modern graph databases adhere to the property graph model and support both directed and undirected graphs.

Graph element

The GQL standard defines a set of fundamental graph elements, each assigned a standard name and optional aliases that can be selected by implementation providers. For consistency and clarity, this book will use a single confirmed name for each element:

• Node, also known as a vertex: In GQL, a node represents an individual entity in the graph, for example, a person, place, or product. Each node can have zero or more labels that classify its role in the data model and can hold properties as key-value pairs to store metadata or descriptive attributes.
• Edge, also known as a relationship: An edge represents a connection or relationship between two nodes, defining how those entities are related. In GQL, edges can...

So far, you’ve explored elements that exist within the graph. In this section, you will delve into additional elements outside the graph using GQL.

The GQL standard also introduces the catalog system, which organizes GQL objects into a structured hierarchy. Catalogs classify objects as either primary or secondary. Understanding this system is crucial for managing and navigating GQL components effectively.

GQL objects

The following list describes the primary and secondary GQL objects (see Figure 2.6 for a diagram of GQL objects):

• Primary GQL objects: These objects may hold other GQL objects. They include the following:
  • GQL directory: Can be the root catalog and contains other GQL directories or GQL schemas
  • GQL schema: Can be the root GQL catalog and contains graph, graph type, binding table, and named procedure
  • Graph and graph type: Represent specific graph instances and their types
  • Binding table...

The graph pattern describes a particular structure of nodes and edges, and their labels and properties. The graph pattern is mainly used for retrieving nodes, edges, paths, and subgraphs within a graph that conforms to it.

Figure 2.9: A MATCH statement with patterns

This example shows a path pattern composed of two node patterns and one edge pattern: (a) and (b) are node patterns to match the nodes and -[:Follows]-> is an edge pattern to match the edges in the paths.

The details of patterns will be discussed in later chapters of this book.

Element patterns

Element patterns are the basic components of a graph pattern and consist of node patterns and edge patterns:

• A node pattern specifies a node to be matched in the graph and is syntactically represented by a pair of parentheses
• An edge pattern specifies an edge to be matched and can be expressed either as a full edge pattern or as an abbreviated form, depending on the inclusion...

This chapter provided a brief introduction to GQL programs, sessions, transactions, and procedures. These concepts may initially seem complex, but they will be explained in greater detail in later chapters. For now, it’s helpful to understand that a GQL program consists of procedures or direct statements executed within a GQL session. A GQL session encompasses context elements such as authorization identifiers, time zones, the current graph, transactions, and other parameters relevant to the GQL request:

• GQL program: A GQL program is a collection of commands and procedures written in GQL, designed to execute specific operations within a GQL environment.
• GQL session: A GQL session is a sequence of GQL requests issued by a GQL agent on behalf of a single user via a GQL client within the same GQL environment.
• GQL transaction: A GQL transaction is a series of actions defined by GQL syntax that must be either fully completed or fully failed. A...

In this chapter, you have gained a foundational understanding of GQL and graph theory, which is crucial for effectively understanding the next chapters. You explored essential graph terminology, the hierarchical design of the GQL catalog system, and how to handle various value types using GQL. Additionally, you learned about GQL patterns and received brief introductions to GQL sessions, transactions, and procedures.

In the next chapter, you will learn how to quickly get started with GQL, executing queries on GQL Playground to create and drop graphs, insert and delete data, and query graph data.