How Padlet uses ClickHouse Cloud to power real-time classroom analytics

Summary

Padlet needed a real-time analytics system to provide teachers with immediate insights into student engagement across 40 million monthly unique users. To avoid the operational overhead of managing database clusters with a small engineering team, the company adopted ClickHouse Cloud and ClickPipes for managed data ingestion. Active user sessions emit 30-second heartbeat events that stream alongside page views into ClickHouse. Materialized views pre-aggregate engagement duration and view counts by date, while native HyperLogLog sketches process unique visitor calculations efficiently across arbitrary time ranges. In production, this architecture ingested roughly eight billion events in a single month and delivered analytical query results with a 45-millisecond median latency.

Context

Padlet serves approximately 40 million monthly active users across 242 countries, generating billions of classroom interaction events. Teachers previously lacked direct access to engagement metrics, requiring manual support requests that took days to resolve. With a 65-person company and no dedicated data team, Padlet needed an automated, cost-effective database capable of low-latency ingestion and sub-second analytical querying at scale.

Approach / What changed

Padlet deployed ClickHouse Cloud with ClickPipes to ingest real-time engagement data without managing backend infrastructure. The engineering team established a 30-second client heartbeat model to record engagement time slices, avoiding complex client-side calculations. To accelerate queries, Padlet configured materialized views with MergeTree engines to pre-aggregate daily view metrics and utilized native HyperLogLog sketches to calculate unique visitor metrics.

Takeaways

• Instead of complex client-side tracking, Padlet measures engagement time by emitting lightweight heartbeat events every 30 seconds to represent fixed engagement slices.
• Padlet uses ClickHouse materialized views to pre-aggregate views and engagement time by date, while computing unique visitors with native HyperLogLog sketches.
• The ClickHouse Cloud architecture handled 8 billion monthly events at 14 requests per second, achieving a 45-millisecond median query latency and a 690-millisecond P99 latency.

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