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Introduction

GrafitoDB is a fast, embeddable property graph database for Python — no server required, SQLite-backed, Cypher-powered, with optional semantic search capabilities.

What is GrafitoDB?

GrafitoDB implements the Property Graph Model (Neo4j-compatible concepts) on top of SQLite, providing a lightweight yet powerful graph database that runs directly in your Python application.

Key Features

Feature Description
No Server Required Embeddable database that runs in-process with your application
SQLite-Backed Reliable storage with ACID transactions
Cypher Query Language Full Cypher parser and executor for declarative queries
Multi-Labeled Nodes Nodes can have multiple labels (e.g., Person, Employee, Manager)
Rich Properties JSON-serializable properties on nodes and relationships
Full-Text Search BM25-ranked keyword search via SQLite FTS5
Semantic Search Vector similarity search with multiple ANN backends
NetworkX Compatible Export to/import from NetworkX for graph algorithms
RDF/Turtle Support Import and export RDF data
Visualization Export to PyVis, D2, Mermaid, and Graphviz

When to Use GrafitoDB

GrafitoDB is ideal for:

  • Prototyping graph-based applications without infrastructure overhead
  • Educational purposes — learning graph databases and Cypher
  • Small to Medium Scale — graphs up to 100K+ nodes
  • Embedded Applications — shipping a graph database with your Python app
  • Testing — graph algorithms without heavy dependencies
  • Hybrid Workflows — combining structured and semantic search

Quick Comparison

Feature GrafitoDB Neo4j NetworkX
Embeddable ✅ Yes ❌ No ✅ Yes
Persistent ✅ Yes ✅ Yes ❌ No
Cypher Support ✅ Full ✅ Full ❌ No
Server Required ❌ No ✅ Yes ❌ No
Vector Search ✅ Built-in Plugin ❌ No
Full-Text Search ✅ FTS5 ✅ Native ❌ No

Philosophy

GrafitoDB follows these design principles:

  1. Simplicity First: Simple installation, simple API, simple mental model
  2. Python-Native: First-class Python integration with familiar patterns
  3. Standards-Based: Cypher queries, SQLite storage, NetworkX compatibility
  4. Extensible: Plugin architecture for embeddings, visualization, and more
  5. Production-Ready: ACID transactions, indexes, constraints, and testing utilities

Next Steps