Scaling Up: When to Migrate from PostgreSQL to a Data Lake

PostgreSQL has been a reliable and accessible choice for handling transactional workloads in data infrastructure due to its rich features and wide adoption. However, as companies grow and require more scalable and efficient solutions for analytical workloads, they may need to consider transitioning to data lakes. Data lakes offer advantages such as better handling of large volumes of data, cost-effective storage, and flexibility in data processing, which are crucial for advanced analytics, machine learning, and rapid organizational iteration. Despite PostgreSQL's strengths, it is not optimized for analytical tasks, and its limitations in scalability and pricing can prompt organizations to migrate to data lakes for enhanced performance and capacity. While data lakes have traditionally been complex and resource-intensive to build, technologies like Starburst Galaxy are making them more accessible and user-friendly, providing an experience akin to cloud data warehouses.