The high-performance database for modern applications
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The Only Native GraphQL Database With A Graph Backend.

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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 for 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 be serving 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.

Use Discuss Issues for reporting issues about this repository.


Dgraph is at version v21.03.0 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.

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:


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

Build and Install

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:

Is Dgraph the right choice for me?

  • 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 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



Client Libraries

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


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