Grafeo: High-Performance Graph Database Built in Rust

Graph databases excel at modeling relationships between entities, making them ideal for infrastructure mapping, service dependencies, and observability data. Grafeo is a new entry in this space, offering exceptional performance through its Rust implementation with zero external dependencies required.

What Is Grafeo?

Grafeo is a high-performance graph database that can run embedded within applications or as a standalone server. Built entirely in Rust, it leverages vectorized execution, adaptive chunking, and SIMD-optimized operations to deliver fast query performance with a minimal memory footprint.

According to benchmarks on the LDBC Social Network Benchmark, Grafeo outperforms other graph databases both in embedded mode and as a server, while using less memory than comparable in-memory solutions.

Key Features for DevOps Teams

Multi-Language Query Support

One standout feature is support for six query languages:

• GQL: ISO standard declarative pattern matching
• Cypher: Neo4j-compatible ASCII-art patterns
• Gremlin: Apache TinkerPop traversal-based queries
• GraphQL: Schema-driven, familiar to web developers
• SPARQL: W3C standard for RDF queries
• SQL/PGQ: SQL:2023 GRAPH_TABLE for SQL-native graph queries

This flexibility means teams can use the query language they already know.

Dual Data Model Support

Grafeo supports both Labeled Property Graphs (LPG) and RDF triples:

# LPG Example - Service Dependencies
MATCH (s:Service {name: 'api-gateway'})-[:DEPENDS_ON]->(dep)
RETURN dep.name, dep.health_status

# RDF Example - Infrastructure Ontology
SELECT ?resource ?status WHERE {
  ?resource infra:type "kubernetes-pod" .
  ?resource infra:status ?status .
  FILTER(?status = "failing")
}

Vector Search

The built-in HNSW-based similarity search with quantization options (Scalar, Binary, Product) enables combining graph traversal with semantic similarity. This proves useful for matching similar incidents or finding related alerts.

ACID Transactions

Full ACID compliance with MVCC-based snapshot isolation ensures data consistency for production workloads. When modeling critical infrastructure relationships, transaction safety matters.

Installation Options

Grafeo offers bindings for multiple languages:

Python:

uv add grafeo

Rust:

cargo add grafeo

Node.js:

npm install @grafeo-db/js

Go:

go get github.com/GrafeoDB/grafeo/crates/bindings/go

Additional bindings exist for C#, Dart, and WebAssembly.

Quick Start Example

Here is a Python example modeling service dependencies:

import grafeo

# Create an in-memory database
db = grafeo.GrafeoDB()

# Define services and dependencies
db.execute("""
  INSERT (:Service {name: 'api-gateway', version: '2.1.0'})
  INSERT (:Service {name: 'auth-service', version: '1.5.2'})
  INSERT (:Service {name: 'user-db', version: '14.2'})
""")

db.execute("""
  MATCH (a:Service {name: 'api-gateway'}), (b:Service {name: 'auth-service'})
  INSERT (a)-[:DEPENDS_ON {critical: true}]->(b)
""")

db.execute("""
  MATCH (a:Service {name: 'auth-service'}), (b:Service {name: 'user-db'})
  INSERT (a)-[:DEPENDS_ON {critical: true}]->(b)
""")

# Find all dependencies of api-gateway
result = db.execute("""
  MATCH (s:Service {name: 'api-gateway'})-[:DEPENDS_ON*]->(dep)
  RETURN DISTINCT dep.name, dep.version
""")

for row in result:
    print(f"Dependency: {row['dep.name']} v{row['dep.version']}")

Use Cases for SRE Teams

Infrastructure Dependency Mapping: Model relationships between services, databases, and infrastructure components. Query paths to understand blast radius during incidents.

Incident Correlation: Store and query incident data with vector search to find similar past incidents and their resolutions.

Change Impact Analysis: Before deploying changes, traverse the dependency graph to identify potentially affected services.

Root Cause Analysis: During outages, query upstream dependencies to quickly identify the failing component.

Architecture Highlights

The database engine includes:

• Push-based execution engine with morsel-driven parallelism
• Columnar storage with type-specific compression
• Cost-based query optimizer with cardinality estimation
• Zone maps for intelligent data skipping

Running as a Standalone Server

Beyond embedded mode, Grafeo runs as a standalone server with REST API and web UI:

grafeo-server --data-dir /var/lib/grafeo --port 7474

This enables integration with existing monitoring and orchestration tools.

Conclusion

Grafeo brings high-performance graph database capabilities to teams that need to model complex relationships without the overhead of traditional solutions. Its Rust foundation provides memory safety and performance, while multi-language query support reduces the learning curve.

For DevOps and SRE teams dealing with increasingly complex infrastructure, a graph database can transform how you understand and troubleshoot your systems.

For more information, visit the Grafeo documentation or check the GitHub repository.

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