2 releases
| 0.1.0-alpha.3 | Oct 12, 2025 |
|---|---|
| 0.1.0-alpha.2 | Oct 4, 2025 |
| 0.1.0-alpha.1 |
|
#2234 in Database interfaces
370 downloads per month
Used in oxirs
7.5MB
171K
SLoC
OxiRS Fuseki
SPARQL 1.1/1.2 HTTP server with Apache Fuseki compatibility
Status: Alpha Release (v0.1.0-alpha.3) - Released October 12, 2025
⚠️ Alpha Software: This is an early alpha release. APIs may change without notice. Not recommended for production use.
Overview
oxirs-fuseki is a high-performance SPARQL HTTP server that provides complete compatibility with Apache Jena Fuseki while leveraging Rust's performance and safety. It implements the SPARQL 1.1 Protocol for RDF over HTTP and extends it with SPARQL 1.2 features.
Features
- SPARQL Protocol Compliance: Full SPARQL 1.1 Protocol implementation
- SPARQL 1.2 Support: Extended features and optimizations
- Fuseki Compatibility: Drop-in replacement for Apache Fuseki
- Multi-Dataset Support: Host multiple datasets on different endpoints
- Authentication & Authorization: Flexible security framework
- GraphQL Integration: Dual protocol support (SPARQL + GraphQL)
- Real-time Features: WebSocket subscriptions and live queries
- High Performance: Async I/O with Tokio and optimized query execution
- Monitoring: Built-in metrics, logging, and health checks
- Configuration: YAML/TOML configuration with hot-reload
Installation
As a Library
[dependencies]
oxirs-fuseki = "0.1.0-alpha.3"
As a Binary
# Install from crates.io
cargo install oxirs-fuseki
# Or build from source
git clone https://github.com/cool-japan/oxirs
cd oxirs/server/oxirs-fuseki
cargo install --path .
Docker
docker pull ghcr.io/cool-japan/oxirs-fuseki:latest
docker run -p 3030:3030 ghcr.io/cool-japan/oxirs-fuseki:latest
Quick Start
Basic Server
use oxirs_fuseki::{Server, Config, Dataset};
use oxirs_core::Graph;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
// Create a dataset with some data
let mut dataset = Dataset::new();
let graph = Graph::new();
dataset.set_default_graph(graph);
// Configure the server
let config = Config::builder()
.port(3030)
.host("localhost")
.dataset("/dataset", dataset)
.build();
// Start the server
let server = Server::new(config);
server.run().await
}
Configuration File
Create fuseki.yaml:
server:
host: "0.0.0.0"
port: 3030
cors: true
datasets:
- name: "example"
path: "/example"
type: "memory"
services:
- type: "sparql-query"
endpoint: "sparql"
- type: "sparql-update"
endpoint: "update"
- type: "graphql"
endpoint: "graphql"
security:
authentication:
type: "basic"
users:
- username: "admin"
password: "password"
roles: ["admin"]
logging:
level: "info"
format: "json"
Run with configuration:
oxirs-fuseki --config fuseki.yaml
API Endpoints
SPARQL Query
POST /dataset/sparql
Content-Type: application/sparql-query
SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 10
SPARQL Update
POST /dataset/update
Content-Type: application/sparql-update
INSERT DATA {
<http://example.org/alice> <http://xmlns.com/foaf/0.1/name> "Alice" .
}
GraphQL
POST /dataset/graphql
Content-Type: application/json
{
"query": "{ person(id: \"alice\") { name, age } }"
}
Data Upload
PUT /dataset/data
Content-Type: text/turtle
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
<http://example.org/alice> foaf:name "Alice" .
Advanced Features
Multi-Dataset Hosting
use oxirs_fuseki::{Server, Config, Dataset};
let config = Config::builder()
.dataset("/companies", Dataset::from_file("companies.ttl")?)
.dataset("/products", Dataset::from_file("products.nt")?)
.dataset("/users", Dataset::memory())
.build();
Authentication
use oxirs_fuseki::{Config, auth::{BasicAuth, JwtAuth}};
let config = Config::builder()
.auth(BasicAuth::new()
.user("admin", "secret", &["admin"])
.user("user", "password", &["read"]))
.build();
Custom Extensions
use oxirs_fuseki::{Server, Extension, Request, Response};
struct MetricsExtension;
impl Extension for MetricsExtension {
async fn before_query(&self, req: &Request) -> Result<(), Response> {
// Log query metrics
Ok(())
}
async fn after_query(&self, req: &Request, response: &mut Response) {
// Add timing headers
}
}
let server = Server::new(config)
.extension(MetricsExtension);
WebSocket Subscriptions
const ws = new WebSocket('ws://localhost:3030/dataset/subscriptions');
ws.send(JSON.stringify({
type: 'start',
payload: {
query: 'SUBSCRIBE { ?s ?p ?o } WHERE { ?s ?p ?o }'
}
}));
ws.onmessage = (event) => {
const data = JSON.parse(event.data);
console.log('New triple:', data);
};
Performance
Benchmarks
Performance Comparison
| Metric | OxiRS Fuseki | Apache Fuseki | Stardog | Improvement |
|---|---|---|---|---|
| Query throughput | 15,000 q/s | 8,000 q/s | 12,000 q/s | 1.9x / 1.25x |
| Memory usage | 45 MB | 120 MB | 80 MB | 2.7x / 1.8x |
| Startup time | 0.3s | 4.2s | 2.1s | 14x / 7x |
| Binary size | 12 MB | 80 MB | 150 MB | 6.7x / 12.5x |
| Cold query latency | 5ms | 25ms | 15ms | 5x / 3x |
| Concurrent connections | 50,000 | 5,000 | 10,000 | 10x / 5x |
Scalability Benchmarks
| Dataset Size | Query Latency (p95) | Memory Usage | Notes |
|---|---|---|---|
| 1M triples | 15ms | 180MB | Excellent |
| 10M triples | 45ms | 1.2GB | Very good |
| 100M triples | 150ms | 8GB | Good |
| 1B triples | 800ms | 32GB | Acceptable |
Benchmarks run on AWS c5.4xlarge instance (16 vCPU, 32GB RAM)
Optimization Tips
use oxirs_fuseki::Config;
let config = Config::builder()
// Enable query caching
.query_cache(true)
.cache_size(1000)
// Optimize for read-heavy workloads
.read_threads(8)
.write_threads(2)
// Enable compression
.compression(true)
.build();
Monitoring
Metrics Endpoint
GET /metrics
Returns Prometheus-compatible metrics:
# HELP sparql_queries_total Total number of SPARQL queries
# TYPE sparql_queries_total counter
sparql_queries_total{dataset="example",type="select"} 1234
# HELP sparql_query_duration_seconds Query execution time
# TYPE sparql_query_duration_seconds histogram
sparql_query_duration_seconds_bucket{le="0.1"} 800
sparql_query_duration_seconds_bucket{le="1.0"} 950
sparql_query_duration_seconds_sum 45.2
sparql_query_duration_seconds_count 1000
Health Checks
GET /health
{
"status": "healthy",
"version": "0.1.0",
"uptime": "2h 15m 30s",
"datasets": {
"example": {
"status": "ready",
"triples": 15420,
"last_update": "2025-01-15T10:30:00Z"
}
}
}
Integration
With oxirs-gql
use oxirs_fuseki::Server;
use oxirs_gql::GraphQLService;
let server = Server::new(config)
.service("/graphql", GraphQLService::new(schema));
With oxirs-stream
use oxirs_fuseki::Server;
use oxirs_stream::EventStream;
let server = Server::new(config)
.event_stream(EventStream::kafka("localhost:9092"));
Deployment
Kubernetes
apiVersion: apps/v1
kind: Deployment
metadata:
name: oxirs-fuseki
spec:
replicas: 3
selector:
matchLabels:
app: oxirs-fuseki
template:
metadata:
labels:
app: oxirs-fuseki
spec:
containers:
- name: oxirs-fuseki
image: ghcr.io/cool-japan/oxirs-fuseki:latest
ports:
- containerPort: 3030
env:
- name: RUST_LOG
value: "info"
resources:
requests:
memory: "64Mi"
cpu: "100m"
limits:
memory: "512Mi"
cpu: "500m"
Docker Compose
version: '3.8'
services:
fuseki:
image: ghcr.io/cool-japan/oxirs-fuseki:latest
ports:
- "3030:3030"
volumes:
- ./data:/data
- ./config.yaml:/config.yaml
environment:
- OXIRS_CONFIG=/config.yaml
- RUST_LOG=info
Performance Tuning
Memory Optimization
# config.yaml
server:
memory:
query_cache_size: "1GB" # Adjust based on available RAM
result_cache_size: "512MB"
connection_pool_size: 100
optimization:
enable_query_planning: true
enable_join_reordering: true
enable_filter_pushdown: true
parallel_execution: true
worker_threads: 8 # Match CPU cores
High-Throughput Configuration
server:
port: 3030
workers: 16 # For CPU-intensive workloads
keep_alive: 30s
request_timeout: 60s
network:
tcp_nodelay: true
socket_reuse: true
backlog: 1024
caching:
query_cache: true
result_cache: true
ttl: 3600 # 1 hour
Production Deployment
security:
tls:
cert_file: "/etc/ssl/certs/server.crt"
key_file: "/etc/ssl/private/server.key"
rate_limiting:
requests_per_minute: 1000
burst_size: 100
logging:
level: "warn" # Reduce log verbosity
format: "json"
audit: true
monitoring:
metrics: true
health_checks: true
profiling: false # Disable in production
Troubleshooting
Common Issues
Q: High memory usage with large datasets A: Enable streaming mode and adjust cache sizes:
query_execution:
streaming_threshold: 10000 # Stream results > 10k rows
max_memory_per_query: "100MB"
Q: Slow query performance A: Enable query optimization and check index usage:
optimization:
query_planner: "advanced"
statistics_collection: true
index_recommendations: true
Q: Connection timeouts A: Adjust timeout settings and connection limits:
server:
connection_timeout: 30s
keep_alive_timeout: 60s
max_connections: 1000
Debug Mode
# Enable debug logging
RUST_LOG=oxirs_fuseki=debug oxirs-fuseki --config config.yaml
# Enable query tracing
oxirs-fuseki --config config.yaml --trace-queries
# Profile performance
oxirs-fuseki --config config.yaml --profile
OxiRS Ecosystem
Core Components
oxirs-core: RDF data model and core functionalityoxirs-arq: SPARQL query engine with optimizationoxirs-shacl: SHACL validation engineoxirs-star: RDF-star and SPARQL-star support
Server & Networking
oxirs-fuseki: HTTP server (this crate)oxirs-gql: GraphQL interface and schema generationoxirs-stream: Real-time data streamingoxirs-federate: Federated query processing
AI & Analytics
oxirs-vec: Vector embeddings and similarity searchoxirs-shacl-ai: AI-powered data validationoxirs-rule: Rule-based reasoning engine
Integration Examples
// Full-stack semantic web application
use oxirs_fuseki::Server;
use oxirs_gql::GraphQLService;
use oxirs_stream::EventStream;
use oxirs_vec::VectorIndex;
let server = Server::new(config)
.service("/graphql", GraphQLService::new(schema))
.event_stream(EventStream::kafka("localhost:9092"))
.vector_index(VectorIndex::new())
.build();
Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
License
Licensed under either of:
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT License (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Status
� Alpha Release (v0.1.0-alpha.3) - October 12, 2025
Current alpha features:
- ✅ SPARQL query/update endpoints backed by persisted N-Quads datasets
- ✅ Federation (
SERVICEclause) with retries,SERVICE SILENT, and result merging - ✅ OAuth2/OIDC + JWT security with hardened headers and HSTS
- ✅ Prometheus metrics, slow-query tracing, and structured logging via SciRS2
- ✅ Multi-dataset support with auto save/load and CLI integration
- 🚧 Advanced admin UI & live reconfiguration (planned for beta)
- 🚧 Authentication system (in progress)
- 🚧 GraphQL integration (in progress)
Note: This is an alpha release. Some features are incomplete and APIs may change.
Dependencies
~206MB
~3.5M SLoC