Amazon S3 cloud object storage has become a popular platform for collecting, analyzing, and retaining diverse enterprise data due to its simplicity, flexibility, and cost-efficiency. Organizations of all sizes are leveraging Amazon S3 to support various use cases such as running cloud-native applications, archiving data, disaster recovery, enterprise security data lakes, and centralizing log data from cloud applications. The rise of object storage can be attributed to factors like adoption of cloud computing, meeting compliance requirements, and the exponential growth of unstructured data. Amazon S3 provides scalability, data protection and storage durability, accessibility, cost-effectiveness, and data security features that make it an attractive option for enterprise data storage. However, challenges such as data visibility, unstructured data format, and data movement and ETL can hinder analytics on Amazon S3 object storage. To overcome these challenges, solutions like Chaos LakeDB are emerging to provide seamless analytics capabilities without physical data movement.