What it does
Dgraph is a native graph database for applications where relationships between entities are central to the data model. It stores properties and edges, supports Dgraph Query Language (DQL), and can generate a GraphQL API from a schema. The official learning path uses a standalone container and the Ratel interface to create and query a small graph. That container is explicitly a quickstart aid, not a production deployment pattern.
Learn the graph model with two connected records
Dgraph's introductory tutorial starts with a person node and a follows edge to another person. Its sample mutation is a useful first task: create Ann with a follows relationship to Ben, then query people with a name predicate. An illustrative DQL query is:
{
people(func: has(name)) {
name
age
}
}
The tutorial demonstrates creating nodes and edges in Ratel and viewing query results. Its standalone Docker image is convenient for learning, but the documentation says it is not recommended for production. Commands and queries here are examples only; nothing was installed or executed for this record.
Choose DQL or schema-first GraphQL deliberately
Use DQL for direct graph operations and traversals. If an application benefits from a typed GraphQL API, Dgraph's GraphQL mode can derive API operations from a schema. The tutorial also describes flexible data entry where predicates can appear before a formal schema is added. That flexibility does not remove the need to decide which fields and relationships your application should rely on.
Separate core use from enterprise features
The current documentation describes enterprise features as proprietary under the Dgraph Community License. Those features are enabled by default for 30 days in a new cluster, then require an enterprise contract to remain enabled. This is a feature-specific licensing statement, not a blanket license classification for every Dgraph component. The official material reviewed did not establish a public price schedule or a complete license map for the rest of the distribution, so check vendor terms before relying on a particular feature.
Strengths
- Graph nodes and edges represent relationships directly, which suits workloads that query connected entities.
- DQL and a schema-first GraphQL API provide different ways to access the graph database.
- The Ratel learning workflow shows mutations and query results visually for a small example graph.
Watch out for
- The documented standalone container is for quickstarts and is not recommended for production.
- Enterprise features require a separate contract after the documented 30-day trial period.
Best for
- Applications whose core queries traverse relationships among users, items, or other connected entities.
- Teams that want a graph database with either direct DQL access or a schema-generated GraphQL API.
- Developers learning graph modeling with a small local tutorial before evaluating a production topology.
Sources
- Dgraph Documentation (Oct 25, 2026)
- Get Started with Dgraph - Introduction | Dgraph Documentation (Oct 25, 2026)
- License | Dgraph Documentation (Oct 25, 2026)
- Dgraph Documentation (Oct 25, 2026)