---
title: "How ChatFeatured migrated from PlanetScale Postgres to Postgres Managed by ClickHouse to power AI brand discovery"
description: "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."
---

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

[Clickhouse](https://yomu.fyi/company/clickhouse) · ClickHouse · May 18, 2026

**Type:** Problem & solution

## 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.

## Context

ChatFeatured needed to support transactional application workloads alongside complex analytics as prompt ingestion and its customer base grew. Its managed Postgres providers became performance or capacity constraints: ingestion pushed CPU usage to 90%, PlanetScale was IOPS-bound, and a 30-day customer analytics query took around two and a half minutes even after denormalization.

## Approach / What changed

The team migrated from PlanetScale to Postgres managed by ClickHouse with the Postgres-to-Postgres ClickPipes connector. The connector performed the initial load, schema transfer, and continuous synchronization, while a five-minute maintenance window completed the cutover. The resulting setup keeps transactional workloads in Postgres and provides a built-in path to sync data to ClickHouse for analytics.

## Takeaways

- ChatFeatured migrated from PlanetScale using ClickPipes, completing the overall migration in 30 minutes with a five-minute maintenance window.
- A 30-day LifestyleRx analytics query improved from around two and a half minutes on PlanetScale to less than one second with ClickHouse.
- ClickHouse compressed ChatFeatured’s CDN log data by 20x, and its analytics performance enabled features such as full customer performance history.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Migrations](https://yomu.fyi/topic/migration), [Performance](https://yomu.fyi/topic/performance), [Postgres](https://yomu.fyi/topic/postgres), [Scalability](https://yomu.fyi/topic/scalability)

- Source: [Clickhouse](https://clickhouse.com/blog/chatfeatured)
- Source URL: https://clickhouse.com/blog/chatfeatured
- Ingested by Yomu: 2026-08-28T01:26:06.557Z

[Read original post](https://clickhouse.com/blog/chatfeatured)