agentdb-vector-search-optimization

skill_id	when-optimizing-vector-search-use-agentdb-optimization
name	agentdb-vector-search-optimization
description	Optimize AgentDB vector search performance using quantization for 4-32x memory reduction, HNSW indexing for 150x faster search, caching, and batch operations for scaling to millions of vectors.
version	1.0.0
category	agentdb
subcategory	performance-optimization
trigger_pattern	when-optimizing-vector-search
agents	["performance-analyzer","ml-developer","backend-dev"]
complexity	intermediate
estimated_duration	5-7 hours
prerequisites	["AgentDB basics","Vector search concepts","Performance profiling skills"]
outputs	["Optimized vector database","4-32x memory reduction","150x faster search","Performance benchmarks"]
validation_criteria	["Memory usage reduced by 4x minimum","Search latency < 10ms (p95)","Throughput > 50K ops/sec","Accuracy maintained > 95%"]
evidence_based_techniques	["Quantitative benchmarking","A/B comparison testing","Performance profiling"]
metadata	{"author":"claude-flow","created":"2025-10-30T00:00:00.000Z","tags":["agentdb","optimization","quantization","hnsw-indexing","performance"]}

AgentDB Vector Search Optimization

Overview

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations for scaling to millions of vectors.

SOP Framework: 5-Phase Optimization

Phase 1: Baseline Performance (1 hour)

• Measure current metrics (latency, throughput, memory)
• Identify bottlenecks
• Set optimization targets

Phase 2: Apply Quantization (1-2 hours)

• Configure product quantization
• Train codebooks
• Apply compression
• Validate accuracy

Phase 3: Implement HNSW Indexing (1-2 hours)

• Build HNSW index
• Tune parameters (M, efConstruction, efSearch)
• Benchmark speedup

Phase 4: Configure Caching (1 hour)

• Implement query cache
• Set TTL and eviction policies
• Monitor hit rates

Phase 5: Benchmark Results (1-2 hours)

• Run comprehensive benchmarks
• Compare before/after
• Validate improvements

Quick Start

import { AgentDB, Quantization, QueryCache } from 'agentdb-optimization';

const db = new AgentDB({ name: 'optimized-db', dimensions: 1536 });

// Quantization (4x memory reduction)
const quantizer = new Quantization({
  method: 'product-quantization',
  compressionRatio: 4
});
await db.applyQuantization(quantizer);

// HNSW indexing (150x speedup)
await db.createIndex({
  : ,
  : { : , :  }
});


db.( ({
  : ,
  : 
}));