AgentDB vs RuVector - Usage Guide

AgentDB vs RuVector - Usage Guide

**DEPRECATION NOTICE:** This document was written for Claude Flow V3. In Turbo Flow V4, Ruflo v3.5 bundles both AgentDB and RuVector — there is no separate installation. All `claude-flow` CLI commands below should be replaced with `npx ruflo@latest` equivalents. See the V4 Quick Reference Guide for current commands. This file is preserved for historical context.

**When to use AgentDB versus RuVector in Claude Flow V3**

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🎯 TL;DR - Quick Decision Matrix

Your Need	Use This	Why
Vector memory storage	AgentDB	Built into Claude Flow, persistent HNSW indexing
Code intelligence (routing, AST, diff)	RuVector	ML-based agent routing, code analysis
Distributed swarms (100+ agents)	RuVector Postgres	Centralized coordination across hosts
Local development (1-15 agents)	AgentDB	Simpler, already installed
Advanced neural (LoRA, EWC++, Flash Attention)	RuVector	Native Rust performance
Simple semantic search	AgentDB	Good enough for most cases

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📊 Overview

What They Are

**AgentDB:**

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**RuVector:**

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🔍 AgentDB - Built-in Vector Memory Storage

What It Is

Vector database component built into `@claude-flow/memory` that provides:

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Core Capabilities

import { AgentDBAdapter, HNSWIndex } from '@claude-flow/memory';

// Initialize vector storage with HNSW indexing
const adapter = new AgentDBAdapter({
  dimension: 1536,
  indexType: 'hnsw',
  metric: 'cosine',
  hnswM: 16,
  hnswEfConstruction: 200
});

// Store memory with embedding
await adapter.store({
  id: 'mem-123',
  content: 'User prefers dark mode',
  embedding: vector,
  metadata: { type: 'preference' }
});

// Semantic search (150x-12,500x faster than brute force)
const memories = await adapter.search(queryVector, {
  limit: 10,
  threshold: 0.7
});

// Cross-agent memory sharing
await adapter.enableCrossAgentSharing({
  shareTypes: ['patterns', 'preferences'],
  excludeTypes: ['secrets']
});

When to Use AgentDB

✅ **Memory & Pattern Storage**

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✅ **Semantic Search**

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