Cost Optimization and Performance Engineering in Lakehouses

Amol Bhatnagar

Abstract: The lakehouse architecture has emerged as a transformative paradigm in modern data platforms, unifying data lake flexibility with data warehouse performance. As organizations deploy increasingly complex data infrastructures, cost optimization and performance engineering have become critical success factors. This paper presents a comprehensive analysis of cost optimization strategies and performance engineering techniques for lakehouse architectures. We examine storage layout optimization through partitioning and clustering strategies, file sizing and compaction methodologies, compute resource management via auto-scaling and workload isolation, query acceleration techniques, and cost governance frameworks. Our analysis demonstrates that properly implemented optimization strategies can reduce total cost of ownership by 40-60% while improving query performance by 3-10x. We provide practical guidance for data platform engineers and architects seeking to maximize the efficiency and cost-effectiveness of their lakehouse implementations.

Keywords: Lakehouse architecture, cost optimization, performance engineering, data platforms, storage optimization, compute scaling, FinOps

How to Cite?: Amol Bhatnagar, "Cost Optimization and Performance Engineering in Lakehouses", Volume 15 Issue 2, February 2026, International Journal of Science and Research (IJSR), Pages: 31-36, https://www.ijsr.net/getabstract.php?paperid=SR26131120623, DOI: https://dx.doi.org/10.21275/SR26131120623