Automated Materialized Views in Dremio

This article examines how Dremio's automated materialized views, called Reflections, address the limitations of traditional cron-based maintenance for lakehouse workloads. It contrasts static scheduled optimization with Dremio's adaptive approach, including Autonomous Reflections that learn from query patterns and automatic table optimization for Iceberg. The piece details why scheduled maintenance fails for unpredictable AI agent queries, how Reflections differ from traditional materialized views, and how to honestly measure performance savings. It positions automated performance optimization as a key enabler for the agentic lakehouse era.