Case Study: Raindrop scales AI observability to petabytes with Tinybird

Raindrop scales AI observability to 100M+ daily requests with Tinybird

Raindrop, a company building an AI observability platform, faced a significant challenge when their initial data infrastructure on Postgres failed under the load of millions of daily events from their first customer. They needed a high-performance solution capable of handling time-series data, fast aggregations, and text search at scale. This led them to adopt the real-time analytics infrastructure from the vendor Tinybird.

By implementing Tinybird, Raindrop migrated their proof-of-concept to a production-ready system in about one week. The solution delivered queries that were 100 to 1000 times faster than Postgres and provided a clean architectural abstraction. The partnership with Tinybird saved Raindrop from needing to hire two to three dedicated engineers, allowing their small team to scale their platform to process hundreds of millions of requests daily.

Raindrop