The cloud has allowed data teams to collect vast quantities of data and store it at reasonable cost, opening the door to new analytics use cases that leverage data lakes, data mesh, and other modern architectures. But for very large volumes of data, generic cloud storage also presents challenges and limitations in how that data can be accessed, managed, and used.Typical blob storage systems in the cloud lack the information required to show relationships between files or how they correspond to a table, making the job of query engines that much harder.