TRANSACTIONAL DATA LAKES: A FRAMEWORK COMPARISON AND ANALYSIS - Raghavendra Gandhi Raketla (INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY (IJRCAIT), 2025)
This comprehensive article explores the evolution and implementation of transactional data lakes as a revolutionary solution to modern enterprise data management challenges. The article examines how organizations are adapting to handle exponentially growing data volumes while maintaining data integrity and enabling real-time analytics. It provides a detailed comparison of leading frameworks including Delta Lake, Apache Iceberg, and Apache Hudi, analyzing their distinct features and performance characteristics. The article also explores industry-specific applications across financial services, healthcare, e-commerce, and telecommunications sectors, highlighting how transactional data lakes are transforming operational efficiency and decision-making capabilities. Additionally, the article addresses implementation challenges, considerations for organizations adopting these technologies, and emerging trends in the field, particularly focusing on artificial intelligence integration, real-time processing capabilities, and cloud-native architectures.