Dremio Lakehouse Modeling

A Dremio lakehouse medallion architecture separates data into Bronze, Silver, and Gold layers. Bronze holds raw data, Silver contains conformed datasets, and Gold serves consumption. You choose between materializing layers as Iceberg tables or virtual views based on query performance and data freshness requirements.

Use Iceberg tables for durable storage, ACID transactions, and upserts via MERGE in Bronze and Silver layers. Use views to apply transformations, combine datasets, and expose semantic layers without duplicating storage, ensuring analytics teams query fresh data without managing physical data copies.

Optimize Dremio query performance by creating reflections to accelerate analytical workloads and applying partitioning strategies to prune data scans. Use LOCALSORT to physically cluster data, and schedule operational commands like OPTIMIZE and VACUUM to compact files and maintain table health.

Implement SCD Type 2 in an Iceberg table using the MERGE statement in Dremio. This pattern tracks historical changes by matching source and target rows, updating existing records to close historical periods, and inserting new rows to capture current dimensional attribute changes accurately.

Dremio supports dimensional modeling by enabling star schema designs for analytics and ML pipelines. You organize semantic layers using views, apply tagging and documentation practices for governance, and expose curated Gold layer datasets to consumption teams for consistent and accurate reporting.