How to create a materialized view

QuestDB is an open-source time-series database designed for high-performance workloads, offering ultra-low latency, high ingestion throughput, and a multi-tier storage engine with native support for Parquet and SQL, ensuring data portability and AI readiness without vendor lock-in. A common usage involves the SAMPLE BY query for computing Open High Low Close (OHLC) prices on dashboards, though high-scale data ingestion and multiple users can strain server capacity. Materialized views are proposed as a solution to optimize aggregation queries by pre-computing and storing query results, thus reducing latency and avoiding repetitive computations. These views refresh automatically with base table updates, making them ideal for real-time dashboards, though they introduce complexities in data freshness and maintenance, especially when base tables change. The text explores creating materialized views, verifying their status, and utilizing advanced patterns like cascading views for performance optimization, while considering trade-offs such as refresh time, storage impact, and query complexity.