Scaling Muse: How Netflix Powers Data-Driven Creative Insights at Trillion-Row Scale

Netflix evolved their Muse analytics platform to handle trillion-row datasets by implementing HyperLogLog sketches for approximate distinct counts, using Hollow for in-memory precomputed aggregates, and extensively tuning their Apache Druid cluster. The migration reduced query latencies by 50% while supporting advanced filtering capabilities for creative content insights. The team used parallel stack deployment, automated validation, and granular feature flags to ensure data accuracy during the transition.