![]() Tables falling into this category include tables registered against data in external systems and tables registered against other file formats in the data lake. These tables are not backed by Delta Lake, and will not provide the ACID transactions and optimized performance of Delta tables. Note that it is possible to create tables on Databricks that are not Delta tables. Because Delta tables store data in cloud object storage and provide references to data through a metastore, users across an organization can access data using their preferred APIs on Databricks, this includes SQL, Python, PySpark, Scala, and R. As Delta Lake is the default storage provider for tables created in Databricks, all tables created in Databricks are Delta tables, by default. A Delta table stores data as a directory of files on cloud object storage and registers table metadata to the metastore within a catalog and schema. To manage data life cycle independently of database, save data to a location that is not nested under any database locations.Ī Databricks table is a collection of structured data. ![]() To avoid accidentally deleting data:ĭo not share database locations across multiple database definitions.ĭo not register a database to a location that already contains data. This interaction between locations managed by database and data files is very important. Successfully dropping a database will recursively drop all data and files stored in a managed location. The LOCATION of a database will determine the default location for data of all tables registered to that database. The LOCATION associated with a database is always considered a managed location.Ĭreating a database does not create any files in the target location. You can optionally specify a LOCATION when registering a database, keeping in mind that: In Databricks, the terms “schema” and “database” are used interchangeably (whereas in many relational systems, a database is a collection of schemas).ĭatabases will always be associated with a location on cloud object storage. Data objects in the Databricks LakehouseĪ database is a collection of data objects, such as tables or views (also called “relations”), and functions.Data discovery and collaboration in the lakehouse. ![]() What does it mean to build a single source of truth?.What is the medallion lakehouse architecture?.What are ACID guarantees on Databricks?. ![]()
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