Why Storing Vectors in PostgreSQL Makes Sense for Many Companies

Vector databases are trending, but for many companies, PostgreSQL with pgvector might be the perfect solution for vector storage needs.

Understanding Vector Storage

What are Vectors?

# Example embedding vector
embedding = [0.1, 0.2, 0.3, ..., 0.768]

PostgreSQL Vector Solutions

Using pgvector

-- Enable pgvector extension
CREATE EXTENSION vector;

-- Create table with vector column
CREATE TABLE items (
  id bigserial PRIMARY KEY,
  embedding vector(384),
  metadata jsonb
);

-- Create HNSW index
CREATE INDEX ON items 
USING hnsw (embedding vector_cosine_ops);

Advantages of PostgreSQL

1. Unified Infrastructure

Single backup system
Familiar monitoring
Existing expertise
Simplified maintenance

2. Transaction Support

BEGIN;
  -- Update both regular and vector data
  UPDATE items SET metadata = '{"updated": true}'
  WHERE id = 1;
  
  UPDATE items SET embedding = '[0.1, 0.2, ...]'
  WHERE id = 1;
COMMIT;

Performance Considerations

Query Performance

-- Similarity search
SELECT id, metadata
FROM items
ORDER BY embedding <-> '[query vector]'
LIMIT 10;

When to Use PostgreSQL for Vectors

Ideal Scenarios

Moderate vector dataset size
Need for ACID compliance
Limited operational complexity
Budget constraints

When to Consider Alternatives

Massive vector datasets
Extreme performance requirements
Specialized similarity search needs

Implementation Guide

1. Setup

# Install pgvector
sudo apt-get install postgresql-14-vector

# Create extension
psql -c 'CREATE EXTENSION vector;'

2. Optimization

-- Optimize for memory
ALTER SYSTEM SET maintenance_work_mem = '1GB';
ALTER SYSTEM SET effective_cache_size = '4GB';

Monitoring and Maintenance

Key Metrics

Query performance
Index size
Cache hit rates
Vector operation timing

Cost Comparison

Traditional Setup

PostgreSQL + pgvector: $50-200/month
Dedicated Vector DB: $200-1000+/month

Conclusion

For many companies, PostgreSQL with pgvector provides a practical, cost-effective solution for vector storage needs without the complexity of managing another database system.

Kartik Gautam