What is a data lake?

A data lake is a flexible and cost-effective data architecture designed to store large volumes of raw data, which can be utilized later for analysis, machine learning, or AI modeling. Unlike databases, which handle daily transactional data, or data warehouses, which require structured data through an ETL process, data lakes support a schema-on-read approach, accommodating structured, semi-structured, and unstructured data. Data lakehouses, seen as the next evolution, enhance data lakes by integrating features typical of data warehouses, such as ACID compliance and version control, using table formats like Apache Iceberg, Delta Lake, and Apache Hudi. While data lakes offer benefits like lower storage costs and flexibility, they also present challenges such as slow query speeds and data governance issues, which data lakehouses aim to address. Technologies like Starburst Galaxy facilitate the management of data lakes and lakehouses by providing tools for storage, compute, metadata management, and data governance, thereby helping organizations efficiently handle and analyze their data.