Databricks Delta Lake Tables: Managed vs Unmanaged

<p>Delta Lake is a powerful storage layer for big data processing workloads in Databricks. In the previous article, we discussed&nbsp;<a href="https://vivekjadhavr.medium.com/delta-lake-on-databricks-python-installation-and-setup-guide-25c9a9bd11ed" rel="noopener">Delta Lake on Databricks: Python Installation and Setup Guide</a><br /> When working with Delta Lake tables, you can choose between two types of tables: managed and unmanaged. In this article, we&rsquo;ll explore the key differences between these two types of tables, and how they&rsquo;re used in Databricks.</p> <h2>Managed Delta Table</h2> <p>Managed Delta Tables are tables whose metadata and data are managed by Delta Lake. You can create a managed Delta table using the SQL API or Python API in Databricks. Managed tables manage the storage and location of data and the table schema. Here&rsquo;s an example of how to create a managed Delta table using the SQL API:</p> <p><a href="https://vivekjadhavr.medium.com/databricks-delta-lake-tables-managed-vs-unmanaged-2fff2b013436"><strong>Website</strong></a></p>