Block vs. Object Storage: A Deep Dive Into the Foundation of Modern Data, and How the Lakehouse Made the Slow Option Fast

This article provides a comprehensive technical analysis of block storage versus object storage, focusing on their mechanical differences, performance characteristics, and real-world use cases. It explains the surprising trend in data analytics where object storage (like Amazon S3), despite higher latency, has become the dominant choice for lakehouses, training sets, and event histories. The article details how technologies like Apache Parquet, Apache Iceberg, and query engines such as Dremio systematically overcome object storage's weaknesses, enabling interactive analytics. It covers latency, throughput, scalability, durability, cost, and consistency with real numbers, and offers practical guidance for evaluating object stores for lakehouse workloads. The content is highly relevant to IT/TECHNOLOGY, focusing on data infrastructure, storage systems, and modern analytics architectures.