Technical Reference
This appendix provides quick-reference materials for implementing and troubleshooting embedding systems at scale.
Vector Database Comparison Matrix
[Table to be added comparing major vector databases across dimensions like: - Maximum scale supported - Indexing algorithms - Query performance - Cost structure - Enterprise features - Cloud vs. self-hosted options]
Embedding Model Benchmarks
[Benchmarking results to be added for popular embedding models across: - Accuracy metrics - Inference latency - Training time - Resource requirements - Domain-specific performance]
Performance Tuning Checklists
Initial Deployment Checklist
Scaling Checklist
Optimization Checklist
Troubleshooting Guide
Query Performance Issues
[Diagnostic steps and solutions to be added]
Training Convergence Problems
[Diagnostic steps and solutions to be added]
Memory and Resource Problems
[Diagnostic steps and solutions to be added]
Glossary of Terms
ANN (Approximate Nearest Neighbor): [Definition to be added]
Contrastive Learning: [Definition to be added]
Embedding: [Definition to be added]
HNSW (Hierarchical Navigable Small World): [Definition to be added]
RAG (Retrieval-Augmented Generation): [Definition to be added]
Siamese Network: [Definition to be added]
Vector Database: [Definition to be added]
[Additional terms to be added]