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Defining how data is physically organized on disk, including sort orders and distribution patterns.
Distinguishing note: The existing candidates focus on UI layouts or build configuration tables, not physical database disk organization.
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Gravitino is a federated metadata lake and unified data catalog designed to manage tables, files, and AI models across diverse data sources and cloud storage. It serves as a centralized interface for governing schemas, access controls, and tagging across relational databases, messaging queues, and object stores. The project distinguishes itself by unifying the management of AI assets, such as machine learning models and their version lineages, alongside traditional tabular data. It also implements the Iceberg REST specification to provide a standardized metadata server and proxy for lakehouse
Defines data distribution and sort orders to optimize how tables organize data on disk.