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 <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’ll explore the key differences between these two types of tables, and how they’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’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>