Operational databases: How they work and when to use them

Operational databases (OLTP) are designed for real-time transaction processing with low latency and high concurrency, contrasting with data warehouses (OLAP) optimized for analytical queries. The post covers core OLTP characteristics, the OLTP vs. OLAP distinction, ETL/CDC pipelines connecting the two, and the limitations of traditional OLTP for modern AI workloads. It then introduces the 'lakebase' concept — specifically Databricks Lakebase — as a unified platform that combines operational and analytical capabilities, supports vector/unstructured data, and enables near-real-time AI use cases without batch pipeline delays.