A COMPARATIVE ANALYSIS OF STORAGE SOLUTIONS: MAPPING OBS AND BLOCK STORAGE TO MODERN CLOUD APPLICATIONS

Abstract

A comprehensive understanding of storage solutions is crucial in today's cloud-driven ecosystem, particularly when optimizing for diverse workloads including AI training and inference operations. This article presents a detailed comparative analysis of Object-Based Storage (OBS) and Block Storage, examining their architectural differences, performance characteristics, and practical applications in modern cloud environments. Through extensive evaluation of scalability, cost efficiency, and data consistency models, this article demonstrates how these storage solutions adapt to various use cases, from web applications to large-scale AI training workloads. This article incorporates real-world case studies and performance metrics from major cloud providers, revealing that while Block Storage excels in low-latency, transaction-intensive operations critical for AI training, OBS proves more cost-effective for large-scale data lakes and inference workloads. This article suggests that a hybrid approach, leveraging both storage types based on specific workload requirements, often yields optimal results in enterprise environments. This article provides technology architects and decision-makers with a framework for selecting appropriate storage solutions while considering factors such as cost optimization, performance requirements, and security compliance.