Comparative Study of Redshift vs. Snowflake: Choosing the Right Data Warehouse for FinTech Applications

Author(s)	Ujjawal Nayak
Country	United States
Abstract	The rapid growth of digital financial services has led to an explosion of transactional, behavioral, and risk-related data. FinTech organizations increasingly rely on cloud data warehouses to support real-time analytics, regulatory reporting, fraud detection, and machine learning–driven decisioning. Among the leading cloud data warehousing platforms, Amazon Redshift and Snowflake are frequently evaluated for FinTech use cases due to their scalability, ecosystem integrations, and advanced security capabilities. This paper presents a comparative study of Amazon Redshift and Snowflake from the perspective of FinTech applications, focusing on architecture, performance, elasticity, security and compliance, data governance, cost models, ecosystem integration, and suitability for common FinTech workloads such as credit risk modeling, payment analytics, fraud detection, and customer 360 views. Based on this analysis, the paper offers guidance on selecting the appropriate platform or adopting a hybrid strategy aligned with specific FinTech requirements.
Keywords	Amazon Redshift, Snowflake, FinTech, Cloud Data Warehousing, Fraud Detection, Credit Risk, Regulatory Reporting, Data Governance.
Field	Engineering
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-01-28
DOI	https://doi.org/10.36948/ijfmr.2026.v08i01.67512

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