dgraph

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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](https://docs.dgraph.io/graphql), and responds in [JSON](http://www.json.org/)
and [Protocol Buffers](https://developers.google.com/protocol-buffers/) over
[GRPC](http://www.grpc.io/) and HTTP. Dgraph is written using the Go Programming Language.

## Status

Dgraph is at [version v25][rel] and is production-ready. Apart from the vast open source community,
it is being used in production at multiple Fortune 500 companies.

[rel]: https://github.com/dgraph-io/dgraph/releases/tag/v25.0.0

## Supported Platforms

Dgraph officially supports the Linux/amd64 and Linux/arm64 architectures. In order to take advantage
of memory performance gains and other architecture-specific advancements in Linux, we dropped
official support for Mac and Windows in 2021, see
[this blog post](https://discuss.dgraph.io/t/dropping-support-for-windows-and-mac/12913) 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 and Linux/arm64 is not available.

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

## Install with Docker

If you're using Docker, you can use the
[official Dgraph image](https://hub.docker.com/r/dgraph/dgraph/).

```bash
docker pull dgraph/dgraph:latest
```

For more information on a variety Docker deployment methods including Docker Compose and Kubernetes,
see the [docs](https://docs.dgraph.io/installation/).

## Run a Quick Standalone Cluster

```bash
docker run -it -p 8080:8080 -p 9080: