Ingesting Massive Data Loads: Patterns for High-Performance Batch Pipelines
· 6 min read
Moving data from source systems into your lake or warehouse sounds simple until you're doing it at scale. A pipeline that works fine at 10M rows starts breaking at 1B — queries time out, storage costs spike, and the pipeline window that should take 2 hours starts taking 14.
This post covers the patterns that separate pipelines that scale from pipelines that collapse under their own weight.