How We Scaled Our PostgreSQL Database to Handle 10M Rows

The Initial Problem

When one of our clients experienced viral growth, their primary dashboard load times degraded from 200ms to 5 seconds. The bottleneck was a PostgreSQL database performing full table scans on a rapidly expanding events table.

The Solutions Implemented

1. Index Optimization: We identified missing composite indexes on frequently filtered columns.
2. Materialized Views: For complex analytical queries that didn't require real-time accuracy, we implemented materialized views refreshed on a schedule.
3. Connection Pooling: We introduced PgBouncer to manage the growing number of simultaneous connections from the serverless edge functions.

The result was a return to 150ms load times and a highly stable infrastructure.