This article outlines Pinterest's transition from a batch-oriented database ingestion system to a real-time, unified framework using Change Data Capture and modern data processing technologies. It addresses the challenges faced with legacy systems and details the architectural improvements that led to lower latency and better resource efficiency.

This article explains how Change Data Capture (CDC) can streamline the process of replicating operational database changes into Apache Iceberg tables. It discusses two main ingestion strategies: direct materialization and using a raw change log with ETL, highlighting the trade-offs between simplicity and flexibility. It also addresses challenges in scaling CDC workloads, including partition layout and update strategies.