Why Batch ELT Breaks at Enterprise Scale

What this post added

This post details the limitations of traditional batch ELT pipelines at enterprise scale, highlighting issues like cascading failures, schema drift, resource inefficiency, and orchestration chaos. It advocates for a streaming-first data integration architecture using Kafka as a durable, scalable, and reusable data movement layer. The post explains how Kafka, combined with connectors and Tableflow, Schema Registry, and open table formats like Iceberg/Delta Lake, can unify operational and analytical data, enabling write-once-read-anywhere data ingestion and reducing the complexity and cost associated with traditional ELT.