Comparative Analysis of Serverless and Container Based Cloud Models for High Throughput Data Processing Applications
Keywords:
Cloud Computing, Serverless, Containers, Data Processing, Scalability, Throughput, PerformanceAbstract
Cloud computing has emerged as the backbone of modern data-driven applications, where high-throughput data processing plays a crucial role in scientific research, enterprise analytics, and large-scale business intelligence. Two dominant paradigms—serverless (Function-as-a-Service, FaaS) and container-based (Container-as-a-Service, CaaS)—offer distinct benefits and limitations for such workloads. This paper presents a comparative analysis of these models with respect to scalability, performance, cost efficiency, and system complexity. The discussion situates both paradigms within the broader landscape of cloud computing. The analysis highlights that while serverless architectures excel in elasticity and cost-efficiency for event-driven workloads, container-based models remain advantageous in achieving consistent performance and greater control for complex, stateful, and high-throughput pipelines.
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Copyright (c) 2022 Anastasia Helen (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
