Open-Source Databases · dgraph-io

dgraph

Dgraph is a distributed, open-source graph database that uses GraphQL syntax and supports real-time queries over large datasets. It provides ACID transactions, automatic replication, and horizontal scaling across multiple nodes, targeting applications with complex relational data that don't fit well into traditional SQL tables.

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Source: GitHub — github.com/dgraph-io/dgraph

21.7k

GitHub stars

1.6k

Forks

Primary language

Apache-2.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	dgraph-io/dgraph
Owner	dgraph-io
Primary language	Go
License	Apache-2.0 — OSI-approved
Stars	21.7k
Forks	1.6k
Open issues	84
Latest release	v25.3.7 (2026-06-25)
Last updated	2026-07-07
Source	https://github.com/dgraph-io/dgraph

What dgraph is

Written in Go, Dgraph implements a sharded, distributed architecture with consistent replication, linearizable reads, and native GraphQL support. It exposes data via gRPC/HTTP with JSON or Protocol Buffers serialization, supports full-text search and geo-spatial queries natively, and handles distributed ACID transactions across a cluster.

Quickstart

Get the dgraph source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/dgraph-io/dgraph.git2cd dgraph3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Knowledge Graphs & Relationship-Heavy Data

Applications requiring traversal of highly connected data (e.g., recommendation engines, identity graphs, knowledge bases) where foreign-key joins in SQL become prohibitive. Dgraph's distributed joins and graph traversals optimize these workloads.

Real-Time Query Performance at Scale

Systems needing sub-second latency on complex queries across terabytes of data. Dgraph's disk layout optimization and distributed sharding reduce seeks and network calls, suitable for user-facing APIs or analytics dashboards.

Flexible Schema with ACID Guarantees

Projects with evolving schemas and sparse data where NoSQL flexibility is needed but transactional consistency cannot be compromised. Dgraph combines both properties without requiring rigid upfront table design.

Implementation considerations

Dgraph requires Go 1.24+ to build from source; Docker deployment is recommended for testing and production to avoid platform-specific build issues.
Schema design and GraphQL query planning differ from SQL; teams should allocate time for GraphQL literacy and understanding Dgraph's query optimizer.
Distributed transactions and consistent replication add latency; measure impact for ultra-low-latency requirements (sub-millisecond) against single-node alternatives.
Data migration from SQL or other graph databases requires custom tooling; no built-in ETL framework is mentioned in the provided data.
Monitoring replication, shard health, and transaction conflicts requires familiarity with distributed systems observability; plan for instrumentation before production.

When to avoid it — and what to weigh

Windows or macOS-only Deployment — Dgraph officially supports only Linux/amd64 and Linux/arm64. Mac and Windows support was dropped in 2021. Docker on these platforms works, but native production deployments are unsupported.
Simple Relational Data — If your data is naturally tabular with few relationships, a relational database (PostgreSQL, MySQL) or simpler OLTP system will have lower operational overhead and faster time to productivity than learning GraphQL and Dgraph's distributed model.
Custom Query Language Preference — Teams already invested in Cypher (Neo4j), Gremlin, or SQL will face a learning curve. Dgraph's GraphQL-inspired syntax is not interoperable with these ecosystems.
Minimal DevOps Capacity — A distributed, sharded database requires operational expertise in clustering, replication monitoring, shard rebalancing, and failure recovery. Single-node databases are far simpler to operate.

License & commercial use

Apache License 2.0 (Apache-2.0). This is a permissive, OSI-approved open-source license allowing commercial use, modification, and distribution with attribution and liability disclaimers. No copyleft restrictions.

Apache 2.0 is a permissive license that permits commercial use without royalty or patent-grant requirements. The README states Dgraph is used in production at multiple Fortune 500 companies. However, there is no explicit commercial support SLA, warranty, or enterprise licensing mentioned in the provided data. For production deployments requiring SLAs, indemnification, or vendor support, contact the Dgraph team directly to confirm commercial support availability and terms.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

The provided data does not document authentication, authorization, encryption at rest, encryption in transit, audit logging, vulnerability disclosure process, or recent security advisories. Before evaluating Dgraph for sensitive data, review the security documentation at docs.dgraph.io, check for CVE disclosures, and assess whether RBAC, network isolation, and encryption mechanisms meet your compliance requirements.

Alternatives to consider

Neo4j

Mature graph database with Cypher query language and strong community. Neo4j Community is GPL v3 (copyleft); Enterprise offers single-server + replicas. Choose Neo4j if you prefer Cypher syntax or need mature tooling, but beware license restrictions and replication limitations in Community edition.

PostgreSQL with PostGIS/pgvector

Relational database with graph extension capabilities (e.g., recursive CTEs, JSON operators, pgvector for embeddings). Better for teams with SQL expertise and modest relationship complexity; simpler operations but less optimized for graph traversals at scale.

JanusGraph

Apache 2.0 licensed graph database layered on pluggable backends (Cassandra, HBase). Offers flexibility and distributed architecture but requires external indexing systems and is less opinionated than Dgraph. Choose if you need deep customization of the underlying storage layer.

Software development agency

Build on dgraph with DEV.co software developers

Dgraph is production-ready and used by Fortune 500 companies, but it requires distributed systems expertise and Linux deployment. Start with Docker, review docs.dgraph.io, and validate that GraphQL syntax and distributed architecture fit your team's workflow. Contact the Dgraph team to confirm commercial support terms if needed.

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dgraph FAQ

Does Dgraph support ACID transactions across a distributed cluster?

Yes. Dgraph provides distributed ACID transactions with consistent replication and linearizable reads, distinguishing it from some competitors like JanusGraph. However, transaction overhead grows with data distribution; benchmark for your latency requirements.

What platforms can I deploy Dgraph on?

Officially: Linux/amd64 and Linux/arm64. Mac and Windows native deployment was dropped in 2021. Docker is the recommended method for testing and production on any platform.

Is there a commercial support option?

The README mentions Fortune 500 companies use Dgraph in production and implies vendor backing, but the provided data does not specify SLAs, support tiers, or contact details. Contact the Dgraph team (via GitHub discussions or official channels) to discuss commercial support, maintenance contracts, or enterprise licensing.

How do I query Dgraph?

Dgraph exposes a GraphQL-inspired query language over gRPC and HTTP, responding in JSON or Protocol Buffers. It also supports RDF. Familiarize yourself with GraphQL syntax; it differs from SQL and Cypher. Official client libraries for multiple languages are available.

Work with a software development agency

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If dgraph is part of your open-source databases roadmap, our team can implement, customize, migrate, and maintain it.

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