Scaling predictive insights: Upollo’s journey from BigQuery to ClickHouse

In 2021, Cayden Meyer led Canva's enterprise, education, and teams efforts. He identified opportunities for conversion, expansion, and retention but found no solution to help him easily focus on these areas. This led him to develop Upollo, a company that predicts who is likely to churn, convert, or expand and why. Upollo serves predictive insights to businesses to help them grow faster and build more effective products. Upollo's mission and offering require the processing and analysis of billions of events, including clicks, page views, billing events, and support interactions. As the company grew, its existing data warehouse, BigQuery, became too costly and inefficient. To keep growing and delivering real-time insights at scale, they needed a more efficient, scalable, and cost-effective solution, which led them to ClickHouse Cloud. Upollo's team established several requirements for their new solution, including affordability, support for real-time data serving without complex workarounds, performance reliability, and an active community backing the platform. They also sought a managed service that would eliminate the need for maintaining the database themselves. After researching alternatives, Upollo decided to give ClickHouse Cloud a shot. The migration was completed in just 30 minutes, and the impact has been significant. ClickHouse's performance made queries up to 20 times faster, unlocked capabilities that were previously unattainable, and simplified Upollo's data architecture by consolidating storage, processing, and serving in one platform. Despite some initial challenges, such as managing memory to avoid out-of-memory (OOM) issues during large queries, Upollo has seen significant improvements in cost efficiency and performance since adopting ClickHouse Cloud. The company plans to continue deepening its relationship with ClickHouse by migrating additional workloads and taking advantage of new features like inverted indexes.