Dgraph Graph Database Cheat Sheet

Distributed graph database Dgraph. GraphQL, DQL, schema, and graph queries.

Last Updated: December 24, 2025

Graph Basics

Nodes, edges, predicates

Key concept 1: graph basics
Comprehensive explanation and practical examples for implementing graph basics in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 2: graph basics
Comprehensive explanation and practical examples for implementing graph basics in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 3: graph basics
Comprehensive explanation and practical examples for implementing graph basics in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 4: graph basics
Comprehensive explanation and practical examples for implementing graph basics in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 5: graph basics
Comprehensive explanation and practical examples for implementing graph basics in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 6: graph basics
Comprehensive explanation and practical examples for implementing graph basics in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.

DQL Queries

Dgraph Query Language, traversals

Key concept 1: dql queries
Comprehensive explanation and practical examples for implementing dql queries in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 2: dql queries
Comprehensive explanation and practical examples for implementing dql queries in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 3: dql queries
Comprehensive explanation and practical examples for implementing dql queries in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 4: dql queries
Comprehensive explanation and practical examples for implementing dql queries in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 5: dql queries
Comprehensive explanation and practical examples for implementing dql queries in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.

GraphQL API

Schema, mutations, queries

Key concept 1: graphql api
Comprehensive explanation and practical examples for implementing graphql api in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 2: graphql api
Comprehensive explanation and practical examples for implementing graphql api in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 3: graphql api
Comprehensive explanation and practical examples for implementing graphql api in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 4: graphql api
Comprehensive explanation and practical examples for implementing graphql api in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 5: graphql api
Comprehensive explanation and practical examples for implementing graphql api in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 6: graphql api
Comprehensive explanation and practical examples for implementing graphql api in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.

Schema

Types, indexes, reverse edges

Key concept 1: schema
Comprehensive explanation and practical examples for implementing schema in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 2: schema
Comprehensive explanation and practical examples for implementing schema in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 3: schema
Comprehensive explanation and practical examples for implementing schema in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 4: schema
Comprehensive explanation and practical examples for implementing schema in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 5: schema
Comprehensive explanation and practical examples for implementing schema in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.

Distributed

Sharding, replication, high availability

Key concept 1: distributed
Comprehensive explanation and practical examples for implementing distributed in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 2: distributed
Comprehensive explanation and practical examples for implementing distributed in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 3: distributed
Comprehensive explanation and practical examples for implementing distributed in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 4: distributed
Comprehensive explanation and practical examples for implementing distributed in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 5: distributed
Comprehensive explanation and practical examples for implementing distributed in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 6: distributed
Comprehensive explanation and practical examples for implementing distributed in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.

Use Cases

Social graphs, knowledge graphs, recommendations

Key concept 1: use cases
Comprehensive explanation and practical examples for implementing use cases in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 2: use cases
Comprehensive explanation and practical examples for implementing use cases in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 3: use cases
Comprehensive explanation and practical examples for implementing use cases in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 4: use cases
Comprehensive explanation and practical examples for implementing use cases in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
Key concept 5: use cases
Comprehensive explanation and practical examples for implementing use cases in production environments. Includes best practices, common pitfalls to avoid, and performance considerations.
💡 Pro Tip: Master the fundamentals of Dgraph Graph Database first before diving into advanced features. Practice with real-world projects and refer to this comprehensive cheatsheet for quick reference and best practices.
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