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Alpha-stage graph database built on SQLite with a fluent query DSL. TypeScript library for modeling connected data with ACID transactions and graph algorithms. Not production-ready yet.

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michaeloboyle/sqlite-graph

sqlite-graph

A high-performance graph database built on SQLite with an intuitive fluent query DSL

License: MIT TypeScript Node.js

Status: 🚧 Under Active Development (Phase 1: Core Implementation)

Overview

sqlite-graph is an alpha-stage graph database library that combines the reliability of SQLite with the expressiveness of a fluent query API. Built with TypeScript and designed for performance, it provides an intuitive way to model and query connected data.

Current Status: Alpha - core functionality working, but not recommended for production use yet.

Key Features:

  • 🚀 Fluent Query DSL - Intuitive method chaining for complex graph queries
  • 📊 Type-Safe - Full TypeScript support with generic types
  • High Performance - Optimized indexes and prepared statements
  • 🔄 ACID Transactions - Built on SQLite's transaction system
  • 🎯 Graph Algorithms - Shortest path, all paths finding, BFS/DFS traversal
  • 🛠️ Universal Schema - Flexible JSON properties for any data model
  • 🔮 Future WASM Support - Path to Rust optimization when needed

Quick Start

import { GraphDatabase } from 'sqlite-graph';

// Initialize database
const db = new GraphDatabase('./graph.db');

// Create nodes
const job = db.createNode('Job', {
  title: 'Senior Engineer',
  status: 'active',
  url: 'https://example.com/job/123'
});

const company = db.createNode('Company', {
  name: 'TechCorp',
  industry: 'SaaS'
});

// Create relationship (natural syntax: job POSTED_BY company)
db.createEdge(job.id, 'POSTED_BY', company.id);

// Query with fluent API
const activeJobs = db.nodes('Job')
  .where({ status: 'active' })
  .connectedTo('Company', 'POSTED_BY')
  .orderBy('created_at', 'desc')
  .limit(10)
  .exec();

// Graph traversal
const similarJobs = db.traverse(job.id)
  .out('SIMILAR_TO')
  .filter(node => node.properties.status === 'active')
  .maxDepth(2)
  .toArray();

// Shortest path
const path = db.traverse(job.id)
  .shortestPath(anotherJob.id);

// Merge operations (upsert)
const { node, created } = db.mergeNode('Company',
  { name: 'TechCorp' },  // Match criteria
  { industry: 'SaaS', size: 'Large' }  // Properties to set
);

// Note: Advanced concurrency features planned for future releases

Installation

⚠️ Not yet published to npm - Currently alpha/development only

# For now, clone and build locally:
git clone https://github.com/michaeloboyle/sqlite-graph.git
cd sqlite-graph
npm install
npm run build
npm test  # 294 tests passing

When published (target: late December 2025):

npm install sqlite-graph

Use Cases

Job Application Pipeline

Track job applications, companies, skills, and their relationships:

const db = new GraphDatabase('./jobs.db', {
  schema: {
    nodes: {
      Job: { properties: ['title', 'url', 'status'] },
      Company: { properties: ['name', 'industry', 'size'] },
      Skill: { properties: ['name', 'category'] }
    },
    edges: {
      POSTED_BY: { from: 'Job', to: 'Company' },
      REQUIRES: { from: 'Job', to: 'Skill' },
      SIMILAR_TO: { from: 'Job', to: 'Job' }
    }
  }
});

// Find similar jobs to rejected applications
const recommendations = db.nodes('Application')
  .where({ status: 'rejected' })
  .with('APPLIED_TO')
  .connectedTo('Job', 'SIMILAR_TO')
  .filter({ status: 'discovered' })
  .exec();

Knowledge Graph

Build wikis, documentation systems, or personal knowledge bases with rich relationships.

Social Networks

Model users, posts, and relationships with efficient graph queries.

Dependency Management

Track software dependencies, versions, and relationships.

Development Methodology

This project uses the SPARC methodology (Specification, Pseudocode, Architecture, Refinement, Completion) with claude-flow for AI-powered development orchestration.

Current Phase: Core Implementation (Phase 1)

Recent progress includes Database class, Transaction support, NodeQuery and TraversalQuery implementations, path finding with cycle detection, and savepoint functionality.

See SPARC-DEVELOPMENT.md for detailed methodology documentation.

Related: claude-flow Issue #821

Documentation

Roadmap

Phase 1: Core Functionality (Complete ✅)

  • Project setup and configuration
  • Type system design
  • Database schema
  • Database class implementation
  • Node/Edge CRUD operations
  • Transaction support with savepoints
  • Path finding with cycle detection
  • Comprehensive test coverage (201 tests passing)

Phase 2: Query DSL (Complete ✅)

  • NodeQuery fluent API
  • TraversalQuery implementation
  • Graph algorithms (BFS, shortest path)
  • Path enumeration (paths() wrapper)
  • Integration tests (13 integration tests)

Phase 3: Advanced Features (Partial ✅)

  • Merge operations (mergeNode, mergeEdge)
  • Index management (createPropertyIndex, dropIndex, listIndexes)
  • Merge operation tests (33 tests passing)
  • Merge operation benchmarks
  • All paths finding (toPaths, allPaths, paths methods)
  • Pattern matching (not implemented)
  • Bulk operations (not implemented)
  • Export/import (implemented in Phase 1)

Phase 3 Status: Core features complete, pattern matching and bulk operations deferred to post-v1.0

Phase 4: Browser Support (v1.0) 🚀 IN PROGRESS

Target: Late December 2024 / Early January 2025

  • Strategic decision: Browser support as competitive moat
  • Research wa-sqlite vs official SQLite WASM
  • Design SQLiteAdapter interface (Node.js + browser)
  • Proof-of-concept: NodeAdapter with 19 passing tests
  • Implement BrowserAdapter (wa-sqlite + OPFS)
  • Convert all APIs to async/await (breaking change)
  • Browser testing with Playwright
  • Demo applications (React PWA, Chrome extension)
  • v1.0.0 release with browser support

Why: Become the ONLY TypeScript graph DB with ACID + algorithms + browser support

See ROADMAP.md for complete 6-week timeline.

Phase 5: Post-v1.0 Polish

  • Community adoption and feedback
  • Missing Phase 3 features (pattern matching, bulk operations)
  • Documentation and examples
  • npm ecosystem presence

Performance

All performance goals met ✅

Goal Target Actual Status
Simple queries <10ms 2.18ms ✅ PASS
Graph traversal <50ms 2.68ms ✅ PASS
Node creation <1ms 286.79µs ✅ PASS
Test coverage >80% 234 tests ✅ PASS

Core Operations:

  • Updates: 38,353 ops/sec
  • Node creation: 3,487 ops/sec
  • Path finding: 12,494 ops/sec

Merge Operations:

  • mergeEdge (match): 37,337 ops/sec
  • mergeEdge (create): 36,485 ops/sec
  • mergeNode (indexed): 29,974 ops/sec
  • mergeNode (create): 6,565 ops/sec
  • Index speedup: 7.11x faster (29,844 vs 4,196 ops/sec)

See BENCHMARKS.md for detailed performance analysis, methodology, and hardware specifications.

Contributing

Contributions are welcome! We follow the Contributor Covenant Code of Conduct.

Getting Started:

  1. Read the Contributing Guide for complete instructions
  2. Check PLAN.md for current roadmap and priorities
  3. Review SPARC-DEVELOPMENT.md for our development methodology
  4. Browse open issues for tasks needing help

Quick Setup:

git clone https://github.com/yourusername/sqlite-graph.git
cd sqlite-graph
npm install
npm test

See CONTRIBUTING.md for detailed contribution guidelines, testing requirements, and PR process.

License

MIT License - see LICENSE for details

Credits

Development Team: Michael O'Boyle and Claude Code Methodology: SPARC with claude-flow Built with: TypeScript, SQLite (better-sqlite3), Jest


Status: 🟡 Alpha - Phase 1-2 Complete, Phase 3 Partial | Phase 4 (Browser Support) In Progress Current Phase: Building v1.0 with universal browser support (6-week timeline) Test Status: 294 tests passing | 2 suites with memory issues | ~75-80% coverage (estimated) Not Production Ready: Memory crashes in coverage tests, missing npm publish config

What Works:

  • ✅ Complete CRUD operations with transactions
  • ✅ Fluent query DSL (NodeQuery, TraversalQuery)
  • ✅ Graph algorithms (BFS, shortest path, cycle detection)
  • ✅ Merge operations (mergeNode, mergeEdge) with index management
  • ✅ Performance benchmarks (all targets exceeded, 7.11x index speedup)
  • ✅ Concurrency utilities (WAL mode, retry logic, write queues)

In Progress:

  • 🚧 Browser support strategy (wa-sqlite + OPFS)
  • 🚧 Adapter pattern POC with TDD (19 tests passing)
  • 🚧 Fixing TraversalQuery memory issues

Known Issues:

  • ⚠️ Jest worker memory crashes on coverage runs (TraversalQuery.test.ts)
  • ⚠️ Not published to npm (missing files field in package.json)
  • ⚠️ Some coverage gaps (Schema.ts, serialization.ts edge cases)

Next: Fix memory issues → npm publish → v1.0.0 with browser support (~6-8 weeks)

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Alpha-stage graph database built on SQLite with a fluent query DSL. TypeScript library for modeling connected data with ACID transactions and graph algorithms. Not production-ready yet.

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