Fast, Transactional, Distributed Graph Database.

Dgraph is a horizontally scalable and distributed graph database, providing ACID transactions, consistent replication and linearizable reads. It's built from ground up to perform for a rich set of queries. Being a native graph 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 be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.

Status

Dgraph is at version 1.1.x 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.

Quick Install

The quickest way to install Dgraph is to run this command on Linux or Mac.

curl https://get.dgraph.io -sSf | bash

Install with Docker

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

docker pull dgraph/dgraph:latest

Install from Source

If you want to install from source, install Go 1.13+ or later and the following dependencies:

Ubuntu:

sudo apt-get update
sudo apt-get install gcc make

Then clone the Dgraph repository and use make install to install the Dgraph binary to $GOPATH/bin.

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

Get Started

To get started with Dgraph, follow:

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

Is Dgraph the right choice for me?

• Do you have more than 10 SQL tables, connected to each other 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 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 compared to other graph DBs

Features	Dgraph	Neo4j	Janus Graph
Architecture	Sharded and Distributed	Single server (+ replicas in enterprise)	Layer on top of other distributed DBs
Replication	Consistent	None in community edition (only available in enterprise)	Via underlying DB
Data movement for shard rebalancing	Automatic	Not applicable (all data lies on each server)	Via underlying DB
Language	GraphQL inspired	Cypher, Gremlin	Gremlin
Protocols	Grpc / HTTP + JSON / RDF	Bolt + Cypher	Websocket / HTTP
Transactions	Distributed ACID transactions	Single server ACID transactions	Not typically ACID
Full Text Search	Native support	Native support	Via External Indexing System
Regular Expressions	Native support	Native support	Via External Indexing System
Geo Search	Native support	External support only	Via External Indexing System
License	Apache 2.0	GPL v3	Apache 2.0

Users

• Dgraph official documentation is present at docs.dgraph.io.
• 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 list of working and planned features.
• Read about the latest updates from Dgraph team on our blog.
• Watch tech talks on our YouTube channel.

Developers

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

Client Libraries

The Dgraph team maintain a number of officially supported client libraries. There are also libraries contributed by the community unofficial client libraries.

Contact

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