International Journal on Science and Technology

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Secure Data Sharing in Financial Services: Redshift Data Sharing vs. Snowflake Secure Data Sharing

Author(s) Ms. Surbhi Gupta, Mr. Ujjawal Nayak
Country United States
Abstract The financial services industry operates in a highly regulated environment that demands secure, compliant, and efficient data exchange to enable critical functions such as credit scoring, fraud detection, risk analytics, and regulatory reporting. As institutions accelerate their cloud transformation journeys, the ability to share data seamlessly across business units, partners, and ecosystems—while maintaining strict control and auditability—has become a strategic imperative.
Modern cloud data platforms such as AWS Redshift and Snowflake have introduced advanced, native data-sharing capabilities that eliminate the need for data duplication and complex ETL pipelines. These features enable real-time collaboration across teams and external stakeholders without compromising on security, governance, or compliance.
This article provides a comprehensive comparison between Amazon Redshift Data Sharing and Snowflake Secure Data Sharing, analyzing their capabilities in security and encryption standards, data governance and lineage, performance and scalability, and regulatory compliance (e.g., GDPR, CCPA, GLBA, SOX). The discussion highlights architectural differences, operational trade-offs, and alignment with financial-sector compliance frameworks.
Keywords Financial Services Industry, Cloud Data Platforms, Data Sharing, AWS Redshift Data Sharing, Snowflake Secure Data Sharing, Data Governance, Regulatory Compliance, Security and Encryption, Risk Analytics, Credit Scoring, Fraud Detection, Regulatory Reporting, Data Lineage, Data Collaboration, Cloud Transformation, GDPR, CCPA, GLBA, SOX, Scalability and Performance
Field Computer > Data / Information
Published In Volume 16, Issue 4, October-December 2025
Published On 2025-10-06
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