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.
The quickest way to install Dgraph is to run this command on Linux or Mac.
curl https://get.dgraph.io -sSf | bashIf you're using Docker, you can use the official Dgraph image.
docker pull dgraph/dgraph:latestIf 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 makeThen 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 installTo 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.
| 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 |
- 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.