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 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 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.
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
Then clone the Dgraph repository and use
make install to install the Dgraph binary to
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.
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
|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|
- 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 list of working and planned features.
- Read about the latest updates from 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.