8-Section Technical Reference for PostgreSQL Vector Search at Scale

This guide focuses on real-world performance problems you’re likely to encounter as PostgreSQL vector search scales, and focused on pgvector.

Performance bottlenecks, common mistakes, indexing choices, and configuration details that matter in real workloads.

8 Sections (Critical Production Problems, Index Type Comparison, Configuration Requirement, Scaling Thresholds, Production Patterns, Monitoring Requirements, Common Mistakes, Decision Framework)

What's covered:

• 5 common production problems

• HNSW vs IVFFlat comparison

• Vector quantization (halfvec, bit, sparsevec)

• PostgreSQL configuration you must tune

• Scaling thresholds

• 3 production patterns with SQL

• Monitoring queries

• 5 common mistakes and fixes

• Decision framework

Available at this price for limited time.

The content is based on hands-on research and production scenarios.

It’s especially valuable for database engineers, ML engineers, and tech leads but in practice, it’s useful for anyone involved in PostgreSQL + vector search discussions, whether internal or with customers.

pgvector, postgresql, vector-search, HNSW, IVFFlat, database-performance, embeddings, technical-guide