GraphAcademy
Course · Part of Sharpen your Cypher

Cypher Indexes and Constraints

Speed up Neo4j queries with Cypher constraints and indexes: uniqueness, node keys, range, composite, text, and full-text indexes, all hands-on.

2 hours27 lessons across 5 modules
CypherSharpen your CypherProcessingIntermediate
About this course

In this 2-hour course, you will learn

This course teaches you how to use Full definition for constraint (opens in a new tab)A rule the database enforces on every node or relationship with a given label or type, rejecting any write that breaks it. and indexes to keep your Neo4j data clean and your Full definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it. queries fast. Over around two hours you will create every major constraint and index type against a live database, verify each one with a hands-on challenge, and learn how the query planner decides which index to use.

Constraints and indexes are two sides of the same mechanism. A constraint stops invalid data entering the graph, and every constraint is implemented internally as an index. An index is a data structure that lets the database retrieve data quickly instead of scanning every Full definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties. or Full definition for relationship (opens in a new tab)A named, directed connection between two nodes. Every relationship has a type, a start node and an end node.. Choosing the right ones for your Full definition for data model (opens in a new tab)The labels, relationship types and properties chosen to represent a domain. is what keeps a graph performing well as it grows, and that is exactly what you practise here.

  • Constraints

    Learn to create uniqueness and node key constraints that enforce data integrity, preventing duplicate or incomplete nodes from entering your graph database.

  • Indexes

    Build range, composite, and text indexes on node properties to dramatically reduce query scan time and speed up Cypher lookups on large datasets.

  • Full-Text Indexes and Search

    Configure full-text indexes powered by Apache Lucene and write Cypher queries that perform relevance-ranked, tokenized searches across multiple node properties.

  • Index Management

    Understand how to list, monitor, and drop indexes and constraints using Cypher, and apply best practices for keeping your schema lean and performant.

Course content

5 modules, 2 hours.

  1. 2 lessons
    1. Constraints and Indexes in Neo4j5 min
    2. Identifying What Constraints and Indexes to Create5 min
  2. 11 lessons
    1. Constraints in Neo4j5 min
    2. Creating Uniqueness Constraints5 min
    3. Creating Uniqueness Constraints5 min
    4. Creating Existence Constraints for Node Properties5 min
    5. Creating Existence Constraints for Node properties5 min
    6. Creating Existence Constraints on Relationship Properties5 min
    7. Creating Existence Constraints for Relationship Properties5 min
    8. Creating Node Key Constraints5 min
    9. Creating a Node Key Constraint5 min
    10. Managing Constraints in Neo4j5 min
    11. Dropping Constraints5 min
  3. 8 lessons
    1. Indexes in Neo4j5 min
    2. Creating Single Property Indexes5 min
    3. Creating a RANGE Index on a Node Property5 min
    4. Creating a RANGE Index on a Relationship Property5 min
    5. Creating Multi-property Indexes5 min
    6. Creating a Composite Index on a Node Property5 min
    7. Creating TEXT Indexes5 min
    8. Using a TEXT index5 min
  4. 3 lessons
    1. Full-text Indexes in Neo4j5 min
    2. Creating and Using Full-text Indexes5 min
    3. Using a full-text Index on a Relationship Property5 min
  5. 3 lessons
    1. Controlling Index Usage5 min
    2. Using query hints5 min
    3. Getting the Most Out of Indexes5 min

  • Who this course is for

    This course is for developers, data engineers, and database administrators who are responsible for a Neo4j database and the queries that run against it. If your application needs to guarantee that an identifier is never duplicated, that every user has a name, or that a lookup which used to be instant does not slow down as the graph grows, the tools you need are Full definition for constraint (opens in a new tab)A rule the database enforces on every node or relationship with a given label or type, rejecting any write that breaks it. and indexes. It is equally useful before and after a problem appears — designing a new graph or rescuing queries that have started to drag. You should already be comfortable writing and profiling Full definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it., up to the level of Intermediate Cypher Queries; the full list of prerequisite courses appears beside this overview.

  • What you'll do

    This is a hands-on course. You work in an embedded sandbox connected to a live Neo4j database loaded with the movie recommendations dataset: Movie, Person, User, and Genre Full definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties. connected by Full definition for relationship (opens in a new tab)A named, directed connection between two nodes. Every relationship has a type, a start node and an end node. such as ACTED_IN, DIRECTED, and RATED.

    Each concept is followed by a challenge. You write the Full definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it. to create a specific Full definition for constraint (opens in a new tab)A rule the database enforces on every node or relationship with a given label or type, rejecting any write that breaks it. or index, and the platform checks the graph to confirm it exists and is defined correctly — you cannot pass by reading alone. Along the way you inspect what you have built with SHOW CONSTRAINTS and SHOW INDEXES, and you compare query plans to see how an index changes the work the database does. By the end you will have created uniqueness constraints, existence constraints, node keys, range indexes, composite indexes, text indexes, and full-text indexes, controlled which index the planner uses with query hints, and dropped the ones a changing Full definition for data model (opens in a new tab)The labels, relationship types and properties chosen to represent a domain. no longer needs.

  • Where to go next

    Full-Text Search in Neo4j builds directly on the full-text index material with a focused, hands-on lab: wildcards, fuzzy matching, boolean operators, and relevance scoring, applied to a working movie search. Full definition for constraint (opens in a new tab)A rule the database enforces on every node or relationship with a given label or type, rejecting any write that breaks it. and indexes also feature in the Neo4j Certified Professional exam, so the skills you prove in this course count toward a recognised credential. Whatever you build next, the habit of constraining your data first and indexing what you query is one you will use in every Neo4j project.

Further reading

Posts from the GraphAcademy blog.

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My five favorite cards in Aura Dashboards

When Dashboards first became available in Aura, I started to move my reporting away from custom tools. Here are the five cards I use the most, and a Cypher statement behind them.

Adam CowleyRead post
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SQL to Cypher - 10 Queries You Already Know

You already know how to write these queries. This article shows you what they look like when the joins go away.

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Writing Cypher Queries That Don't Lose Your Data

The query trap that hides your newest data, and the query shape that brings it back.

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