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Data Consistency Models in Distributed Systems: CAP Theorem Revisited

Author(s) Pradeep Bhosale
Country United States
Abstract As modern applications demand global scalability, low latency, and fault tolerance, distributed systems have become ubiquitous in cloud computing, microservices, and large-scale data management solutions. However, ensuring correct and predictable data access in these environments is challenging due to network partitions, asynchronous communication, and diverse workload patterns. Data consistency models define the guarantees applications can expect when reading and writing data distributed across multiple nodes. The CAP theorem, formulated two decades ago, offers a theoretical lens to understand the trade-offs between Consistency, Availability, and Partition tolerance. Yet, evolving system architectures, new protocols, and hybrid consistency approaches have emerged since CAP’s initial articulation, prompting a re-examination of these concepts. This paper revisits the CAP theorem, exploring a broad spectrum of consistency models from strong consistency and linearizability to eventual and causal consistency. We illustrate how modern distributed databases, content delivery networks, and geo-replicated storage systems implement nuanced consistency semantics. Through diagrams, tables, and case studies, we highlight how system designers navigate the complexity of consistency trade-offs to meet application-level requirements. Ultimately, understanding these consistency models enables architects and engineers to make informed decisions balancing correctness, performance, availability, and user experience in large-scale distributed systems.
Keywords Distributed Systems, Consistency Models, CAP Theorem, Fault Tolerance, Scalability, Linearizability, Eventual Consistency, Replication, Cloud Computing
Field Engineering
Published In Volume 14, Issue 3, July-September 2023
Published On 2023-07-05
Cite This Data Consistency Models in Distributed Systems: CAP Theorem Revisited - Pradeep Bhosale - IJSAT Volume 14, Issue 3, July-September 2023. DOI 10.5281/zenodo.14631471
DOI https://doi.org/10.5281/zenodo.14631471
Short DOI https://doi.org/g8zdqz
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