Mintlify boosts NPS 30% and saves 60% with real-time analytics on ClickHouse Cloud

Summary

Documentation platform Mintlify experienced major dashboard performance degradation and rate limiting under PostHog as multi-tenant analytics traffic grew rapidly. Because PostHog lacked incremental materialized views, queries scanned full raw datasets and took tens of seconds to load. Mintlify migrated its customer-facing analytics infrastructure to ClickHouse Cloud, ingesting events through Amazon MSK and ClickPipes into a single events table backing incremental materialized views. The team executed the transition over two weeks by dual-writing events and replicating the existing PostHog schema to preserve API surface compatibility. The migration reduced dashboard query latency to sub-one-second, decreased related support bug reports to zero, lifted NPS by an estimated 30%, and lowered analytics infrastructure costs by approximately 60%.

Context

Mintlify powers developer documentation and help centers for tens of millions of monthly users, with AI agents generating roughly half of its traffic. As its customer base expanded, the embedded PostHog product analytics setup struggled with multi-tenant querying. Lacking incremental materialized views, dashboards ran expensive queries against raw datasets, leading to high latency exceeding tens of seconds and frequent rate limit errors.

Approach / What changed

Mintlify migrated to ClickHouse Cloud over a two-week period. The engineering team dual-wrote events to PostHog and ClickHouse while matching the PostHog schema and handler APIs one-to-one to ensure parity. Events stream through Amazon MSK into ClickHouse via ClickPipes, feeding into a single events table with incremental materialized views to serve real-time dashboard analytics and an internal Slack bot.

Takeaways

• Replicating existing event schemas and API handler mappings allowed Mintlify to dual-write and validate queries in parallel without major API refactoring.
• Using ClickHouse incremental materialized views over a single base events table avoided expensive raw dataset scans and eliminated dashboard rate limits.
• Streaming events through Amazon MSK via ClickPipes into ClickHouse Cloud reduced analytics infrastructure costs by around 60% while eliminating routine operational overhead.

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