How Dgraph Documentation Supports Operating and Administering Dgraph

Dgraph Documentation (docs.dgraph.io) is the official documentation site for Dgraph, an open-source, distributed, highly available graph database built for real-time workloads and terabyte-scale data. For operations and administration work, the site's Dgraph DB section is the primary path: it covers getting started, using, and operating the database directly, while the separate GraphQL API section is aimed at schema-driven application development rather than cluster administration. If your job is running, scaling, or maintaining a Dgraph deployment, start in the Dgraph DB section; if you are generating an API layer from a GraphQL schema, the GraphQL API section is the relevant one.

What the documentation covers

The site presents two distinct paths, and the split matters for administrators:

The documentation describes Dgraph as open-source, scalable, distributed, highly available, and designed for real-time workloads and horizontal scalability. It is implemented as a distributed system that processes queries in parallel. Those properties are exactly what shape the operational tasks you will need documentation for.

Where to look for administration and operations content

Because the site organizes content under the Dgraph DB heading, that section is where to find material on getting started, using, and operating the database. When you need to answer a specific operational question, map it to the property it touches:

• Distributed operation — Dgraph runs as a distributed system, so expect operational content to address multi-node concerns rather than single-process setup.
• High availability — availability is a stated design property, so look for guidance framed around keeping the database serving under failure rather than only initial installation.
• Real-time workloads — the database is positioned for real-time use cases, which means operational guidance is oriented toward latency-sensitive serving, not batch-only analytics.
• Horizontal scalability — scaling out is a design goal, so capacity and growth questions belong with the scalability material rather than the application-development path.

Choosing between the two paths

Use this as a decision rule rather than a preference:

• Choose Dgraph DB when your task is direct database operations or administration — running, operating, and managing the database itself.
• Choose GraphQL API when your task is rapid application development with a schema-driven API generated from your GraphQL schema.

These are complementary, not competing: the same deployment can be administered through the Dgraph DB path while applications consume it through a generated GraphQL API. The documentation's own framing is "choose your path," so pick based on whether your immediate problem is operating the database or building against it.

Practical starting point

1. Open docs.dgraph.io and identify which of the two headings — Dgraph DB or GraphQL API — matches your task.
2. For operations and administration, enter through Dgraph DB, which the site describes as covering getting started, use, and operation.
3. Frame your question in terms of the documented design properties (distributed, highly available, real-time, horizontally scalable) so you land on the right operational topic.
4. Treat the GraphQL API section as the destination only when your goal is generating an API and graph backend from a schema.

Limits to keep in mind

The available site material establishes the structure and positioning of the documentation but does not enumerate specific administration commands, configuration parameters, or version-specific procedures. For those details, work from the Dgraph DB section itself rather than assuming coverage from the overview. Pricing and access terms are not stated in the source material, so do not assume the documentation or the database is free or requires no login based on this overview alone.