https://github.com/dgraph-io/dgraph
high-performance graph database for real-time use cases
https://github.com/dgraph-io/dgraph
database distributed go knowledge-graph
Last synced: 3 days ago
JSON representation
high-performance graph database for real-time use cases
- Host: GitHub
- URL: https://github.com/dgraph-io/dgraph
- Owner: dgraph-io
- License: apache-2.0
- Created: 2015-08-25T07:15:56.000Z (over 10 years ago)
- Default Branch: main
- Last Pushed: 2026-03-27T15:20:46.000Z (9 days ago)
- Last Synced: 2026-03-28T00:35:48.461Z (9 days ago)
- Topics: database, distributed, go, knowledge-graph
- Language: Go
- Homepage: https://dgraph.io
- Size: 631 MB
- Stars: 21,623
- Watchers: 358
- Forks: 1,589
- Open Issues: 53
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md
- Audit: audit/audit.go
- Codeowners: .github/CODEOWNERS
- Security: SECURITY.md
Awesome Lists containing this project
- go-awesome - Dgraph - 分布式图数据库 (开源类库 / 数据库)
- go-awesome-with-star-updatetime - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Advanced Console UIs)
- stars - dgraph-io/dgraph - performance graph database for real-time use cases (HarmonyOS / Windows Manager)
- awesome-go-cn - dgraph - io/dgraph) [![godoc][D]](https://godoc.org/github.com/dgraph-io/dgraph) (数据库 / Go中实现的数据库)
- my-awesome - dgraph-io/dgraph - graph pushed_at:2026-02 star:21.6k fork:1.6k high-performance graph database for real-time use cases (Go)
- fucking-awesome-go - :octocat: dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. :star: 1258 :fork_and_knife: 49 (Database / Advanced Console UIs)
- awesome-go-cn - dgraph
- awesome-awesomeness - Dgraph
- awesome - dgraph - Fast, Distributed Graph DB (Go)
- awesome-go-storage - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database)
- awesome-go - dgraph-io/dgraph
- awesome-go - dgraph - | - | - | (Database / Advanced Console UIs)
- awesome-go - Dgraph - 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. (Distributed Data Stores)
- awesome-list - Dgraph - Native GraphQL Database with graph backend. (Data Management & Processing / Database & Cloud Management)
- awesome-go - dgraph - Fast, Distributed Graph DB - ★ 6881 (Database)
- awesome-go-storage - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. Stars:`21.3K`. (Database / Databases Implemented in Go)
- go-awesome - Dgraph - Distributed graph database (Open source library / Database)
- awesome-go - dgraph-io/dgraph - performance graph database for real-time use cases ☆`21,399` (Database / Databases Implemented in Go)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Databases Implemented in Go)
- fucking-awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Databases Implemented in Go)
- awesome - dgraph - Fast, Distributed Graph DB (Go)
- awesome-starred - dgraph-io/dgraph - The high-performance database for modern applications (golang)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Databases Implemented in Go)
- awesome-bigdata - DGraph - A scalable, distributed, low latency, high throughput graph database aimed at providing Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. (Graph Data Model)
- awesome-starts - dgraph-io/dgraph - Native GraphQL Database with graph backend (Go)
- awesome - dgraph-io/dgraph - high-performance graph database for real-time use cases (Go)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Advanced Console UIs)
- fucking-awesome-bigdata - DGraph - A scalable, distributed, low latency, high throughput graph database aimed at providing Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. (Graph Data Model)
- awesome-bigdata - DGraph - A scalable, distributed, low latency, high throughput graph database aimed at providing Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. (Graph Data Model)
- A-curated-list-of-awesome-big-data-frameworks-ressources-and-other-awesomeness.- - DGraph - A scalable, distributed, low latency, high throughput graph database aimed at providing Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. (Graph Data Model)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Advanced Console UIs)
- data-engineering-collection - DGraph - A scalable, distributed, low latency, high throughput graph database aimed at providing Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. (Graph Data Model)
- awesome-repositories - dgraph-io/dgraph - high-performance graph database for real-time use cases (Go)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Databases Implemented in Go)
- awesome-go-cn - dgraph
- awesome-go-extra - dgraph - 08-25T07:15:56Z|2022-08-25T19:46:51Z| (Generators / Databases Implemented in Go)
- awesome-bigdata - DGraph - A scalable, distributed, low latency, high throughput graph database aimed at providing Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. (Graph Data Model)
- awesome-rainmana - dgraph-io/dgraph - high-performance graph database for real-time use cases (Go)
- awesome-go-processed - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database.| (Database / Advanced Console UIs)
- awesome-bigdata - DGraph - A scalable, distributed, low latency, high throughput graph database aimed at providing Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. (Graph Data Model)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Databases Implemented in Go)
- awesome-list - dgraph - io | 16489 | (Go)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Databases Implemented in Go)
- awesome-golang-repositories - dgraph
- awesome-go-cn - dgraph - io/dgraph) [![godoc][D]](https://godoc.org/github.com/dgraph-io/dgraph) (数据库 / Go中实现的数据库)
- awesome-go-with-stars - dgraph - 03-06 | (Data Integration Frameworks / Databases Implemented in Go)
- awesome-go - dgraph - 可扩展,分布式,低延迟,高吞吐量图形数据库。 (<span id="数据库-database">数据库 Database</span> / <span id="高级控制台用户界面-advanced-console-uis">高级控制台用户界面 Advanced Console UIs</span>)
- awesome-ccamel - dgraph-io/dgraph - high-performance graph database for real-time use cases (Go)
- awesome-go-plus - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database.  (Database / Databases Implemented in Go)
- awesome - dgraph-io/dgraph - high-performance graph database for real-time use cases (<a name="Go"></a>Go)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Databases Implemented in Go)
- awesome-go-info - dgraph
- awesome-Char - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Advanced Console UIs)
- awesome-go - dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database. (Database / Advanced Console UIs)
README

[](https://github.com/dgraph-io/dgraph/stargazers)
[](https://github.com/dgraph-io/dgraph/commits/main/)
[](https://goreportcard.com/report/github.com/dgraph-io/dgraph)
[](https://hub.docker.com/r/dgraph/dgraph)
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 9080:9080 -v ~/dgraph:/dgraph dgraph/standalone:latest
```
## Install from Source
If you want to install from source, install Go 1.24+ or later and the following dependencies:
### Ubuntu
```bash
sudo apt-get update
sudo apt-get install build-essential
```
### Build and Install
Then clone the Dgraph repository and use `make install` to install the Dgraph binary in the
directory named by the GOBIN environment variable, which defaults to $GOPATH/bin or $HOME/go/bin if
the GOPATH environment variable is not set.
```bash
git clone https://github.com/dgraph-io/dgraph.git
cd dgraph
make setup
make install
```
## Get Started
**To get started with Dgraph, follow:**
- [Installation to queries in 4 quick steps](https://docs.dgraph.io/quick-start).
- Tutorial and presentation videos on
[YouTube channel](https://www.youtube.com/playlist?list=PLzOEKEHv-5e3u2Tgv52O2rs5u3md58JON).
## 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 |
| 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](https://docs.dgraph.io).**
- For general information and questions, visit
[Github discussions](https://github.com/dgraph-io/dgraph/discussions).
- Please see [releases tab](https://github.com/dgraph-io/dgraph/releases) to find the latest release
and corresponding release notes.
## Developers
Please see [Contributing to Dgraph](https://github.com/dgraph-io/dgraph/blob/main/CONTRIBUTING.md)
for guidelines on contributions.
## Client Libraries
The Dgraph team maintains several
[officially supported client libraries](https://docs.dgraph.io/clients/). There are also libraries
contributed by the community
[unofficial client libraries](https://docs.dgraph.io/clients/unofficial-clients).
##
## Contact
- Please use [Github discussions](https://github.com/dgraph-io/dgraph/discussions) for questions,
feature requests and discussions.
- Please use [GitHub Issues](https://github.com/dgraph-io/dgraph/issues) for filing bugs or feature
requests.