Get Started with Lakebase

This get started course introduces Databricks Lakebase, a fully managed PostgreSQL service built into the Databricks Data Intelligence Platform that brings operational (OLTP) and analytical (OLAP) workloads closer together.

The course begins with a conceptual lecture that compares OLTP and OLAP systems, explaining their different performance characteristics, storage models, and typical use cases. You will also explore the challenges organizations face when maintaining separate transactional databases and analytical platforms, including data movement, latency, and architectural complexity.

You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.

Through hands-on labs, you will:

Create and explore a Lakebase project using autoscaling compute

• Navigate the Lakebase UI, including branching, monitoring, and configuration settings

• Create and query tables using the Lakebase SQL Editor

• Query Lakebase data from Databricks using Lakehouse Federation and foreign catalogs

• Perform Reverse ETL by synchronizing Delta tables to Lakebase

• Connect to Lakebase from Python and perform basic CRUD operations

This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.

By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.

Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.