Databricks lakehouse8/9/2023 ![]() ![]() Unity Catalog metastore: Unity Catalog provides centralized access control, auditing, lineage, and data discovery capabilities. Azure Databricks provides the following metastore options: The metastore contains all of the metadata that defines data objects in the lakehouse. Function: saved logic that returns a scalar value or set of rows.įor information on securing objects with Unity Catalog, see securable objects model.View: a saved query typically against one or more tables or data sources.Table: a collection of rows and columns stored as data files in object storage.Databases contain tables, views, and functions. Database or schema: a grouping of objects in a catalog.There are five primary objects in the Databricks Lakehouse: The Databricks Lakehouse architecture combines data stored with the Delta Lake protocol in cloud object storage with metadata registered to a metastore. What data objects are in the Databricks Lakehouse? Learn more about how this model works, and the relationship between object data and metadata so that you can apply best practices when designing and implementing Databricks Lakehouse for your organization. This model combines many of the benefits of an enterprise data warehouse with the scalability and flexibility of a data lake. ![]() The Databricks Lakehouse organizes data stored with Delta Lake in cloud object storage with familiar relations like database, tables, and views. ![]()
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