Case Study: Canva built user-facing analytics 10x cheaper and 5x faster with Tinybird
Key results
The challenge
Canva ran a warehouse-centric data platform that could not meet the latency and concurrency requirements for user-facing analytics at reasonable cost. It needed an engine purpose-built for real-time, in-product analytics, separate from its business intelligence and data science workloads.
The solution
Canva moved its user-facing analytics use cases to Tinybird, ingesting large event volumes and exposing low-latency SQL-based API endpoints to power in-product Insights features for creators.
“When we moved those use cases to Tinybird, we shipped them 5x faster and at a 10x lower cost than our prior approach.”
GNGuy NeedhamStaff Backend Engineer, Canva
The results, in context
Canva reported 10x lower compute costs and shipped user-facing analytics 5x faster than its prior approach, cutting end-to-end latency 25,000x from a monthly batch to real time. It held sub-50ms p99 API latency while processing 1.4PB per month and 31M requests per day, and shipped 7 new features in a year.