Understanding Databricks Lakehouse Platform Architecture and Security

🔑 Data reliability and performance are crucial in the Databricks Lakehouse platform.

🏢 Data Lakes lack important features for reliability and performance compared to data warehouses.

🔒 Databricks solves these issues with Delta Lake and Photon technologies.

The Databricks Lakehouse platform ensures synchronized data and prevents conflicting changes.

Photon is a query engine that provides improved speed and performance for various data workloads.

Unified governance and security are essential for protecting data and preventing breaches.

🔑 Databricks offers Unity catalog as a unified governance solution for all data assets, providing fine-grained access control and centralized governance.

🔍 Unity catalog enables easy data search and discovery, with low latency metadata serving and faster processing compared to hive metastore.

🔗 Data lineage in Unity catalog allows for tracking the origin, transformations, and dependencies of data, facilitating error investigation and impact analysis.

Databricks developed Delta sharing as an open source solution to share live data securely across different platforms.

Delta sharing allows sharing of existing data in Delta Lake and Apache Parquet formats, without the need for new ingestion processes.

Delta sharing provides centralized administration and governance, allowing tracking and auditing of data usage at different levels.

The Databricks Lakehouse platform ensures data security through a control plane and data plane architecture and encrypted communication.

The networking infrastructure of the data plane is managed by Databricks for serverless compute environments.

🔒 The Databricks Lakehouse platform architecture ensures security by using hardened system images and unprivileged containers.

🔑 Databricks provides various ways to access data, including table ACLS, instance profiles, and the secrets API.

🌐 Databricks offers isolation and governance at different levels, such as workspace and cluster levels, to ensure security and compliance.

🔑 Databricks has released a serverless compute option, called Databricks SQL, which is a fully managed service that handles compute resources.

💻 The serverless compute resource is elastic and scalable, with three layers of isolation for security and is terminated after each use.

📚 The Databricks Lakehouse Platform utilizes Delta Lake and Unity Catalog for data storage, management, and governance.

🔑 The Databricks Lakehouse Platform architecture includes a three-level namespace: catalogs, schemas, and data objects.

📊 Tables in Databricks have two variations: managed tables and external tables, based on where the table data is stored.

🔒 Databricks uses Delta sharing, an open protocol, for secure data sharing across organizations.