When to use a data lakehouse architecture

A data lakehouse architecture merges the benefits of data lakes and data warehouses, offering a flexible, cost-effective solution for managing large volumes of data across various formats. It is built on object storage and utilizes the separation of storage and compute principles, which helps prevent issues like data swamps common in traditional data lakes. Starburst's data lakehouse enables organizations to overcome scalability and vendor lock-in constraints by incorporating open table formats, optionality, and native security, allowing for seamless integration with multiple data sources and cloud environments. This architecture supports performance efficiency through features like cluster autoscaling and compatibility with ANSI SQL for data transformation, making it suitable for both interactive and long-running queries. The structure of a data lakehouse involves a three-layer approach—land, structure, and consume—which helps in organizing data efficiently for reporting purposes. Starburst Galaxy, built on the Trino engine, enhances the data lakehouse experience by providing scalable and secure data management solutions while integrating with tools like Great Expectations, dbt, Airflow, and Dagster to ensure robust data pipelines.