Introduction
LatticeDB is the world’s first production-grade hybrid graph/vector database that runs entirely in the browser with zero backend required.
What is LatticeDB?
LatticeDB combines two powerful database paradigms into a single, unified engine:
- Vector Search Engine - HNSW-based approximate nearest neighbor search with SIMD acceleration
- Graph Database - Full Cypher query language support with BFS/DFS traversal
This hybrid approach enables powerful use cases that neither paradigm can achieve alone, such as:
- Finding similar documents AND their relationships
- Semantic search with graph-based re-ranking
- Knowledge graphs with embedding-based similarity
Key Features
Browser-Native Execution
LatticeDB compiles to WebAssembly and runs entirely in the browser:
- Zero server costs - No backend infrastructure required
- Sub-millisecond latency - No network round-trips
- Privacy by default - Data never leaves the user’s device
- Offline-capable - Works without internet connectivity
Extreme Performance
LatticeDB is faster than industry-standard databases:
| vs Qdrant (Vector) | Speedup |
|---|---|
| Search | 1.4x faster |
| Upsert | 177x faster |
| Retrieve | 52x faster |
| Scroll | 7.4x faster |
| vs Neo4j (Graph) | Speedup |
|---|---|
| Node MATCH | 62x faster |
| Filter queries | 5-45x faster |
| ORDER BY | 8x faster |
API Compatibility
- Qdrant-compatible REST API - Drop-in replacement for existing vector search apps
- Cypher query language - Familiar syntax for graph operations
- Rust, TypeScript, and Python client libraries
Use Cases
RAG Applications
Build retrieval-augmented generation apps that run entirely in the browser:
User Query → Vector Search → Context Retrieval → LLM Response
Knowledge Graphs
Create and query knowledge graphs with semantic similarity:
MATCH (doc:Document)-[:REFERENCES]->(topic:Topic)
WHERE doc.embedding <-> $query_embedding < 0.5
RETURN doc, topic
Personal AI Assistants
Build privacy-preserving AI assistants where all data stays local:
- Chat history with semantic search
- Personal knowledge bases
- Offline-capable reasoning
Architecture Overview
┌─────────────────────────────────────────────────┐
│ LatticeDB │
├─────────────────────────────────────────────────┤
│ ┌─────────────┐ ┌─────────────┐ │
│ │ Vector │ │ Graph │ │
│ │ Engine │◄──►│ Engine │ │
│ │ (HNSW) │ │ (Cypher) │ │
│ └─────────────┘ └─────────────┘ │
├─────────────────────────────────────────────────┤
│ Unified Storage Layer │
│ (MemStorage | DiskStorage | OPFS) │
└─────────────────────────────────────────────────┘
Getting Started
Ready to dive in? Start with the Installation guide.
License
LatticeDB is dual-licensed under MIT and Apache 2.0. Choose whichever license works best for your project.