Case Study: Upollo achieves faster, more cost-effective predictive analytics with ClickHouse

Scaling predictive insights Upollo’s journey from BigQuery to ClickHouse

Upollo, a predictive analytics company that helps businesses forecast churn, conversion, and expansion, needed a better way to process billions of events across more than 40 terabytes of data. Its existing BigQuery and Postgres setup had become expensive, slow, and operationally complex, creating latency and duplicated work as the team scaled its real-time insights service.

Upollo migrated its core data to ClickHouse Cloud, using ClickPipes to ingest large batches of event data quickly and consolidating storage, processing, and serving into one platform. With ClickHouse, queries became up to 20x faster, large count queries dropped from tens of seconds to fractions of a second, and data batches could be loaded in minutes—helping Upollo cut costs, reduce engineering overhead, and scale more efficiently.

Upollo

Cayden Meyer

Founder & CEO