dgraph-io/dgraph

The Only Native GraphQL Database With A Graph Backend.

Dgraph is a horizontally scalable and distributed GraphQL database with a graph backend. It provides ACID transactions, consistent replication, and linearizable reads. It's built from the ground up to perform a rich set of queries. Being a native GraphQL database, it tightly controls how the data is arranged on disk to optimize for query performance and throughput, reducing disk seeks and network calls in a cluster.

Dgraph's goal is to provide Google production-level scale and throughput, with low enough latency to serve real-time user queries over terabytes of structured data. Dgraph supports GraphQL query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP. Dgraph is written using the Go Programming Language.

Dgraph is at version v23.1.0 and is production-ready. Apart from the vast open source community, it is being used in production at multiple Fortune 500 companies, and by Intuit Katlas and VMware Purser. A hosted version of Dgraph is available at https://cloud.dgraph.io.

Dgraph officially supports the Linux/amd64 architecture. Support for Linux/arm64 is in development. In order to take advantage of memory performance gains and other architecture-specific advancements in Linux, we dropped official support Mac and Windows in 2021, see this blog post for more information. You can still build and use Dgraph on other platforms (for live or bulk loading for instance), but support for platforms other than Linux/amd64 is not available.

Running Dgraph in a Docker environment is the recommended testing and deployment method.

If you're using Docker, you can use the official Dgraph image.

docker pull dgraph/dgraph:latest

For more information on a variety Docker deployment methods including Docker Compose and Kubernetes, see the docs.

docker run -it -p 8080:8080 -p 9080:9080 -v ~/dgraph:/dgraph dgraph/standalone:latest

If you want to install from source, install Go 1.19+ or later and the following dependencies:

sudo apt-get update
sudo apt-get install build-essential

Then clone the Dgraph repository and use make install to install the Dgraph binary in the directory named by the GOBIN environment variable, which defaults to $GOPATH/bin or $HOME/go/bin if the GOPATH environment variable is not set.

git clone https://github.com/dgraph-io/dgraph.git
cd dgraph
make install

To get started with Dgraph, follow:

• Installation to queries in 3 steps via dgraph.io/docs/.
• A longer interactive tutorial via dgraph.io/tour/.
• Tutorial and presentation videos on YouTube channel.

• Do you have more than 10 SQL tables connected via foreign keys?
• Do you have sparse data, which doesn't elegantly fit into SQL tables?
• Do you want a simple and flexible schema, which is readable and maintainable over time?
• Do you care about speed and performance at scale?

If the answers to the above are YES, then Dgraph would be a great fit for your application. Dgraph provides NoSQL like scalability while providing SQL like transactions and the ability to select, filter, and aggregate data points. It combines that with distributed joins, traversals, and graph operations, which makes it easy to build applications with it.

• Dgraph official documentation is present at dgraph.io/docs/.
• For feature requests or questions, visit https://discuss.dgraph.io.
• Check out the demo at dgraph.io and the visualization at play.dgraph.io.
• Please see releases tab to find the latest release and corresponding release notes.
• See the Roadmap for a list of working and planned features.
• Read about the latest updates from the Dgraph team on our blog.
• Watch tech talks on our YouTube channel.

• See a list of issues that we need help with.
• Please see Contributing to Dgraph for guidelines on contributions.

The Dgraph team maintains several officially supported client libraries. There are also libraries contributed by the community unofficial client libraries.

• Please use discuss.dgraph.io for documentation, questions, feature requests and discussions.
• Please use discuss.dgraph.io for filing bugs or feature requests.
• Follow us on Twitter @dgraphlabs.