Comparative Analysis of E-Auction Platforms: Technologies, Features, and Performance

Abstract

E-auction platforms have transformed the conventional auction techniques through facilitating online bidding, improving accessibility, and enhancing market efficiency. This research paper offers a comparative study of some of the popular E-Auction platforms, including their technological foundations, core functionality, and overall performance metrics. The research compares different models of auctions such as English, Dutch, Sealed-Bid, and Reverse Auctions, noting their applications and efficiency across industries. The article discusses the backend and frontend technologies employed in contemporary E-Auction systems, contrasting frameworks such as Django along with database options such as SQL vs. NoSQL (MongoDB, Firebase, MySQL, PostgreSQL). Furthermore, the research compares critical features, such as real-time bidding, security measures, fraud detection systems, and user experience aspects. In order to evaluate performance and scalability, the paper performs benchmarking tests on various platforms, examining aspects including response time, bid processing rate, server load management, and security vulnerabilities. Additionally, the study examines the contributions of AI, machine learning, and blockchain towards strengthening the security and efficiency of online auctions. The research provides valuable input on the strengths and shortcomings of current E-Auction systems, enabling developers, enterprises, and researchers to comprehend which technologies and functionalities make an auction platform successful. The research concludes with suggestions for improving E-Auction systems through the inclusion of advanced security features, AI-based bidding algorithms, and cloud-based scalable architectures for better performance and reliability.