Open-Source Databases · vesoft-inc

nebula

NebulaGraph is a distributed, open-source graph database designed to handle large-scale data with millisecond-level latency. It separates storage and compute, scales horizontally, and supports OpenCypher-compatible queries. It is used for social networks, recommendation systems, knowledge graphs, and security applications.

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Source: GitHub — github.com/vesoft-inc/nebula

12.3k

GitHub stars

1.3k

Forks

C++

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	vesoft-inc/nebula
Owner	vesoft-inc
Primary language	C++
License	Apache-2.0 — OSI-approved
Stars	12.3k
Forks	1.3k
Open issues	678
Latest release	v3.8.0 (2024-05-17)
Last updated	2026-05-18
Source	https://github.com/vesoft-inc/nebula

What nebula is

Written in C++, NebulaGraph uses symmetric distribution, RAFT-based strong consistency, and storage-compute separation for horizontal scalability. It provides role-based access control, graph analytics algorithms, and a query language compatible with OpenCypher. The architecture divides responsibility among meta, storage, and compute nodes.

Quickstart

Get the nebula source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/vesoft-inc/nebula.git2cd nebula3# follow the project's README for install & configuration

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

Best use cases

Social Network & Recommendation Systems

Handle relationship queries (friend graphs, connection recommendations) with low-latency traversal and sub-millisecond response times across billions of vertices and edges.

Knowledge Graph & Entity Resolution

Store and query interconnected entities and relationships at scale; support complex link analysis across industries (finance, healthcare, research).

Security & Fraud Detection

Perform rapid graph traversal for anomaly detection, capital flow tracking, and multi-hop relationship discovery across large transaction and entity networks.

Implementation considerations

Requires operational expertise: cluster deployment, RAFT configuration, and monitoring across meta, storage, and compute nodes.
Graph schema design and nGQL query optimization are critical; poor modeling can degrade traversal performance significantly.
Ensure sufficient hardware resources (memory, disk, network bandwidth) for the expected graph size; horizontal scaling requires adding nodes and rebalancing.
Plan for backup, restore, and disaster recovery; RAFT replication provides data protection but operational procedures must be established.
Consider learning curve for teams unfamiliar with graph semantics and nGQL; tooling ecosystem (Studio, exchange tools) can ease adoption.

When to avoid it — and what to weigh

Simple Relational Queries — If your data model and queries fit standard OLTP or OLAP relational databases, the operational overhead of a graph database is not justified.
Single-Node or Embedded Requirements — NebulaGraph is designed for distributed deployment; embedding a single-node instance for lightweight applications introduces unnecessary complexity.
Unstructured or Document-Centric Data — If the primary use case is document storage or text search rather than relationship traversal, document databases or search engines are better fits.
Strict Transactional ACID Guarantees Across Relations — NebulaGraph emphasizes distributed strong consistency via RAFT but is optimized for read-heavy graph traversal, not complex multi-step transactions.

License & commercial use

NebulaGraph is licensed under Apache License 2.0 (Apache-2.0), a permissive open-source license that permits commercial use, modification, and distribution with minimal restrictions. The license explicitly allows deploying NebulaGraph as a backend service for SaaS offerings.

Apache 2.0 permits commercial deployment, modification, and SaaS use without royalties or proprietary restrictions. No closed-source licensing requirement. However, review the license terms and consult legal counsel if you plan to redistribute modified versions or bundle it with proprietary software. Vesoft offers commercial support and cloud services separately.

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	High
DEV.co fit	Good
Assessment confidence	High

Security considerations

NebulaGraph supports role-based access control (RBAC) for authorization. Data is protected in transit and at rest via standard TLS/encryption mechanisms (specifics not detailed in provided data). Distributed architecture over RAFT ensures strong consistency but does not eliminate attack surface; network segmentation, firewall rules, and credential management are operator responsibilities. No documented security audit or CVE history provided; assess based on your risk profile and threat model.

Alternatives to consider

Amazon Neptune

Fully managed AWS graph database; trades operational overhead for vendor lock-in and proprietary APIs. Best for teams wanting minimal ops burden.

JanusGraph

Open-source distributed graph database with pluggable backends (Cassandra, HBase); more mature ecosystem and stronger ACID guarantees, but steeper learning curve.

Neo4j

Market-leading property graph database; simpler to deploy on single/small clusters, rich query language and tooling, but commercial licensing for distributed features.

Software development agency

Build on nebula with DEV.co software developers

Our engineers can help you architect a distributed graph infrastructure, optimize nGQL queries, and manage deployment on your cloud platform. Let's build your graph system.

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nebula FAQ

Is NebulaGraph suitable for sub-million-vertex graphs?

Yes, NebulaGraph works well for small to large graphs. However, operational overhead (cluster management, RAFT consensus) may not be justified for very small datasets; single-instance deployments are available but not recommended for production.

Can NebulaGraph be deployed on Kubernetes?

Not clearly stated in provided data. Requires review of deployment documentation, Helm charts, or operator resources. Check the ecosystem tools and community discussions for Kubernetes-native deployment options.

What is the performance impact of RAFT replication?

RAFT consensus ensures strong data consistency but incurs network round-trip latency. Query performance depends on cluster configuration, graph topology, and nGQL optimization. Benchmark your specific workload in a test environment.

How do I migrate from another graph database (e.g., Neo4j)?

Data migration strategies (Nebula Exchange, custom ETL scripts, nGQL import tools) are available but not detailed in provided data. Requires careful schema mapping and validation. Consult official migration guides or community resources.

Work with a software development agency

Adopting nebula is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate open-source databases software in production.

Ready to Deploy NebulaGraph?

Our engineers can help you architect a distributed graph infrastructure, optimize nGQL queries, and manage deployment on your cloud platform. Let's build your graph system.

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