An overview of Lakehouse Architecture
Date:
The presentation explains the transition from traditional SQL-based data warehouses to a lakehouse architecture, highlighting the roles of DBT, Trino, and Apache Iceberg in building a modern data platform.
Motivation: Why Move to a Lakehouse
- Traditional warehouses have limitations in scalability, flexibility, and cost.
- A lakehouse combines:
- Data lake scalability (cheap storage, flexibility)
- Warehouse reliability (ACID guarantees, structured querying)
- Goal: unified platform for raw + processed + analytics-ready data.
Technology Choices (Rationale)
- Parquet → efficient columnar storage
- Iceberg → reliable table management on object storage
- Trino → fast distributed SQL query engine
- DBT → structured, maintainable transformation workflows
