How Object Storage Became the Backbone of Fast Modern Analytics

Despite being 50–100 times slower in latency than block storage, object storage like Amazon S3 has become the dominant foundation for the world's analytical data systems over the past decade. Block storage, used in cloud services such as AWS EBS, offers sub-millisecond response times and is essential for transactional databases, but its architecture limits scalability and sharing across machines. Object storage trades raw speed for massive scalability, lower cost, and high durability, making it attractive for large-scale data lakes and lakehouses. Engineers addressed object storage's latency drawbacks through innovations in file formats like Apache Parquet, table formats like Apache Iceberg, and query engines such as Dremio. Together, these technologies systematically neutralized object storage's weaknesses, enabling interactive analytics at scale without reverting to costlier block-based infrastructure.