How ChatFeatured migrated from PlanetScale Postgres to Postgres Managed by ClickHouse to power AI brand discovery

Summary

ChatFeatured, a Toronto-based startup, helps brands track and improve how AI models discover and recommend them, including by analyzing cited sources and guiding content production. As prompt ingestion grew to about 1,000 prompts daily across six AI models, managed Postgres instances became slow, CPU reached 90% during ingestion windows, and PlanetScale hit an IOPS limit; analytics queries remained the deeper constraint. The team migrated from PlanetScale to Postgres managed by ClickHouse using the Postgres-to-Postgres ClickPipes connector, which handled initial load, schema transfer, continuous sync, and a five-minute maintenance window; the migration took 30 minutes overall. This setup retains Postgres for transactional workloads while providing a built-in path to ClickHouse for analytics, and a 30-day LifestyleRx query fell from about two and a half minutes to less than a second, with 20x compression reported for CDN log data.

Takeaways

1. 1

   ChatFeatured migrated from PlanetScale using ClickPipes, completing the overall migration in 30 minutes with a five-minute maintenance window.

2. 2

   A 30-day LifestyleRx analytics query improved from around two and a half minutes on PlanetScale to less than one second with ClickHouse.

3. 3

   ClickHouse compressed ChatFeatured’s CDN log data by 20x, and its analytics performance enabled features such as full customer performance history.