Introduction

Founded in 2008, Airbnb transformed the hospitality sector by establishing a global platform that allowed owners and guests to connect and share lodging. Managing its IT infrastructure became extremely difficult as the company's user base swelled to over 150 million active users worldwide and it produced enormous volumes of data every day. About 1.5 petabytes of big data, including user interactions, reservations, property listings, reviews, and financial transactions, were being processed by Airbnb by 2023. Improving client experiences, streamlining processes, and spurring innovation all depended on this data. The original infrastructure, however, was not built to support such a magnitude. Regular server failures, outages during periods of high traffic, and scaling issues made it difficult for Airbnb to provide flawless services. Furthermore, in the rapidly evolving travel industry, the requirement for real-time analytics to dynamically modify pricing and customize customer experiences become more and more important. In order to overcome these obstacles, Airbnb started a revolutionary process to create a scalable data architecture by utilizing state-of-the-art technology and cloud services such as Amazon Web Services (AWS). This case study explores the technological tactics used by Airbnb to get over these obstacles and demonstrates the observable results of its data engineering initiatives.