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Getting Started with the Graph Query Language (GQL)
Getting Started with the Graph Query Language (GQL)

Getting Started with the Graph Query Language (GQL): A complete guide to designing, querying, and managing graph databases with GQL

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Profile Icon Ricky Sun Profile Icon Jason Zhang Profile Icon Yuri Simione
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€37.99
Paperback Aug 2025 392 pages 1st Edition
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€26.98 €29.99
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€37.99
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Arrow left icon
Profile Icon Ricky Sun Profile Icon Jason Zhang Profile Icon Yuri Simione
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€37.99
Paperback Aug 2025 392 pages 1st Edition
eBook
€26.98 €29.99
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€37.99
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Free Trial
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€26.98 €29.99
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Getting Started with the Graph Query Language (GQL)

Summary

In this chapter, we explored how database query languages have evolved, moving from relational and NoSQL models to the emergence of the graph model. We looked at the challenges traditional databases face when handling complex relationships and how graph databases provide a more intuitive way to manage interconnected data. By tracing the history of data management—from early record-keeping methods to the rise of SQL—we set the stage for understanding why GQL has become necessary and how it’s shaping the future of data querying.Next, we’ll dive into the fundamentals of GQL and graph theory. We’ll cover essential graph terminology, explore the structure of the GQL catalog system, and see how different value types are handled in GQL. The chapter also includes executable GQL code, giving you a chance to try things out in your own environment or with GQL Playground by Ultipa Graph.

Graph terms and definitions

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...

GQL catalog system

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...

Graph patterns

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

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...

Other topics

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...

Summary

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.

...

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Key benefits

  • Go beyond theory and apply key concepts and syntax through interactive tutorials and practical examples via the GQL Playground
  • Leverage advanced features of GQL to manipulate graph data efficiently
  • Explore GQL applications in data analytics and discover how to leverage graph knowledge in real-world scenarios
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Graph Query Language is becoming the go-to standard for graph databases, especially with its support for interconnected analytics and GenAI capabilities. This book comes from a team of industry veterans who know exactly how to break down the fundamental GQL concepts, graph terms, definitions, catalog systems, and everything that matters in actual work. You’ll get to grips with graph data types, value expressions, graph matching patterns, and modifying statements through practical GQL examples. With access to the GQL Playground via Ultipa Graph, you’ll get hands-on experience querying and manipulating graph data. Once you've got the basics down, you’ll tackle advanced GQL topics such as path modes, complex path matching patterns, shortest path queries, composite statements, session and transaction commands, and procedures. You’ll also learn to create extensions and understand the design of graph databases to solve industry issues. The authors cover techniques like property graphs to help you optimize your graph queries and offer insights into the future of GQL and graph technology. By the end of this book, you’ll confidently query and update graph data, run graph algorithms, and create visualizations. Plus, you’ll apply your learnings to a real-world use case of money flow analysis for assessing bank client behaviors and detecting transaction risks.

Who is this book for?

This book is for graph database developers, DBAs, programmers, data engineers, and analysts who want to learn the new graph database standard GQL. A basic understanding of graph and relational databases, data models, knowledge of SQL basics, and programming will make the content easy to grasp. While it is designed to be accessible even if you don’t have a background in graph theory, familiarity with concepts like nodes, edges, relationships, and the distinction between directed and undirected graphs will enhance your learning experience.

What you will learn

  • Experiment with GQL syntax on GQL Playground, including MATCH, RETURN, INSERT, UPDATE, and DELETE
  • Work with operators, functions, and variables in an organized fashion
  • Become familiar with complex topics such as varying path matching modes, repeated variables, shortest path, procedures, and transactions
  • Enhance execution speed through indexing or caching systems
  • Understand how to manage access control effectively
  • Tackle real-world issues with a case study focused on money transaction analytics
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Table of Contents

16 Chapters
Evolution Towards Graph Databases Chevron down icon Chevron up icon
Key Concepts of GQL Chevron down icon Chevron up icon
Getting Started with GQL Chevron down icon Chevron up icon
GQL Basics Chevron down icon Chevron up icon
Exploring Expressions and Operators Chevron down icon Chevron up icon
Working With GQL Functions Chevron down icon Chevron up icon
Delve into Advanced Clauses Chevron down icon Chevron up icon
Configuring Sessions Chevron down icon Chevron up icon
Graph Transactions Chevron down icon Chevron up icon
Conformance to the GQL Standard Chevron down icon Chevron up icon
Beyond GQL Chevron down icon Chevron up icon
A Case Study – Anti-Fraud Chevron down icon Chevron up icon
The Evolving Landscape of GQL Chevron down icon Chevron up icon
Glossary and Resources Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
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