Delta Lake is an open format storage layer that delivers reliability, security and performance on your data lake — for both streaming and batch operations. By replacing data silos with a single home for structured, semi-structured and unstructured data, Delta Lake is the foundation of a cost-effective, highly scalable lakehouse.

In this demo, we’ll show you how Delta Lake works and its main capabilities:

• ACID transactions
• Support for DELETE/UPDATE/MERGE
• Unify batch and streaming
• Time travel
• Clone zero copy
• Generated partitions
• CDF (change data flow) (DBR runtime)
• Delta 3.0: Blazing-fast queries with Liquid Clustering, automatically creating your partitions without skew
• Delta 3.0: Universal Format allowing other formats to natively read your Delta Lake tables, without lockin (Uniform)

To install the demo, get a free Databricks workspace and execute the following two commands in a Python notebook

%pip install dbdemos

import dbdemos
dbdemos.install('delta-lake')

Dbdemos is a Python library that installs complete Databricks demos in your workspaces. Dbdemos will load and start notebooks, Delta Live Tables pipelines, clusters, Databricks SQL dashboards, warehouse models … See how to use dbdemos

Dbdemos is distributed as a GitHub project.

For more details, please view the GitHub README.md file and follow the documentation.
Dbdemos is provided as is. See the License and Notice for more information.
Databricks does not offer official support for dbdemos and the associated assets.
For any issue, please open a ticket and the demo team will have a look on a best-effort basis.