Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
As enterprises increasingly distribute their data and workloads across on-premises and cloud environments, achieving the right balance between performance and economic efficiency has become a defining challenge in modern data strategy. Hybrid cloud data architectures allow organizations to combine the control and security of local systems with the elasticity and innovation of cloud platforms. However, realizing this potential requires deliberate design choices that optimize cost, scalability, and operational performance.
This article examines the core principles of hybrid cloud data architecture, emphasizing design strategies, cost-governance models, and performance optimization methods. Drawing insights from real-world implementations—particularly in the banking and financial sectors—it illustrates how enterprises can achieve agility and compliance while containing costs. The discussion also explores key challenges such as latency, interoperability, vendor lock-in, and data sovereignty, and highlights emerging trends like AI-driven infrastructure management, edge computing, and zero-trust security frameworks.
By presenting a structured and practical approach, this study serves as a reference for IT leaders and data architects seeking to build resilient, high-performing, and financially sustainable hybrid ecosystems.
Keywords:
hybrid cloud architecture, performance optimization, cost governance, multi-cloud, edge computing, data sovereignty, AI automation
Cite Article:
"Balancing Performance and Economics in Hybrid Cloud Data Architectures", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 2, page no.135-148, February-2022, Available :http://www.ijrti.org/papers/IJRTI2202021.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator