ESEILANE is a next-generation, high-performance Knowledge Graph engine purpose-built for Large Language Models (LLMs), GraphRAG, and AI-native applications.
Leveraging sparse matrix algebra and linear algebra-based query execution, ESEILANE delivers sub-millisecond graph traversals at scale.
| Feature | Description |
|---|---|
| Ultra-Low Latency | Sub-millisecond response times powered by GraphBLAS sparse matrix algebra |
| GraphRAG Native | First-class integration with LLMs — reduce hallucinations, improve AI accuracy |
| Property Graph Model | Nodes and relationships with rich attributes, full OpenCypher support |
| Horizontal Scale | Pay-as-you-grow distributed architecture with zero-overhead multi-tenancy |
| Enterprise Ready | Role-based access control, audit logging, encryption at rest and in transit |
| Rust Core | Next-gen engine rewritten in Rust for maximum performance and memory safety |
docker run -p 6379:6379 -p 3000:3000 eseilane/eseilane:latestpip install eseilanefrom eseilane import ESEILANE
db = ESEILANE(host='localhost', port=6379)
g = db.select_graph('KnowledgeBase')
g.query("""
CREATE (:Entity {name:'Artificial Intelligence'})-[:RELATED_TO]->(:Domain {name:'Machine Learning'}),
(:Entity {name:'GraphRAG'})-[:ENHANCES]->(:Entity {name:'Artificial Intelligence'})
""")
results = g.query("""
MATCH (e:Entity)-[:ENHANCES]->(ai:Entity)
WHERE ai.name = 'Artificial Intelligence'
RETURN e.name, ai.name
""")
for row in results.result_set:
print(f"{row[0]} enhances {row[1]}")npm install eseilane-jsimport { ESEILANE } from 'eseilane-js';
const db = new ESEILANE({ host: 'localhost', port: 6379 });
const graph = db.selectGraph('KnowledgeBase');
const result = await graph.query('MATCH (n:Entity) RETURN n.name LIMIT 10');
console.log(result.data);┌─────────────────────────────────────────────────────────────┐
│ ESEILANE Core │
│ │
│ ┌─────────────┐ ┌──────────────┐ ┌───────────────┐ │
│ │ Query Layer │ │ Graph Engine │ │ Storage Layer │ │
│ │ (Cypher / │──▶│ (GraphBLAS │──▶│ (Sparse │ │
│ │ REST / │ │ + Rust) │ │ Matrix / │ │
│ │ GraphQL) │ └──────────────┘ │ RDB Hybrid) │ │
│ └─────────────┘ └───────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ LLM Integration Layer │ │
│ │ GraphRAG · Embeddings · Semantic Search · RAG │ │
│ └─────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
from eseilane.graphrag import GraphRAGClient
client = GraphRAGClient(db_host="localhost", llm_provider="openai", model="gpt-4o")
client.ingest("""
ESEILANE is a high-performance knowledge graph engine.
It integrates with LLMs to power GraphRAG applications.
GraphRAG reduces hallucinations by grounding responses in structured knowledge.
""")
response = client.query("How does ESEILANE reduce LLM hallucinations?")
print(response.answer)
print(response.graph_context)| Operation | ESEILANE | Neo4j | ArangoDB |
|---|---|---|---|
| Node Lookup (1M nodes) | 0.8ms | 4.2ms | 3.1ms |
| 3-hop Traversal | 2.1ms | 12.4ms | 9.8ms |
| Cypher Query (complex) | 5.3ms | 28.7ms | 21.2ms |
| Bulk Insert (1M edges) | 1.2s | 8.6s | 5.4s |
| GraphRAG Context Build | 120ms | 890ms | 640ms |
Benchmarks run on AWS r6i.4xlarge. Results may vary by workload.
- Core graph engine (GraphBLAS)
- OpenCypher query support
- Python & JavaScript SDKs
- Docker & cloud deployment
- Multi-tenancy & RBAC
- Rust engine GA (Q3 2026)
- Native vector index (Q3 2026)
- GraphQL API (Q4 2026)
- Managed cloud — ESEILANE Cloud (Q4 2026)
- Federated graphs (2027)
We love contributions! See CONTRIBUTING.md and CODE_OF_CONDUCT.md.
Found a vulnerability? Read SECURITY.md and report privately — do not open a public issue.
ESEILANE is released under the Apache License 2.0.
Built with care by Simpl3x3 · eseilane.org