Understanding Databricks Lakehouse Platform Architecture and Security
This video introduces the Databricks Lakehouse Platform Architecture and Security, highlighting the benefits of using the platform and introducing Photon, the next-generation query engine. It explains the challenges of data sharing and the limitations of existing technologies, and discusses the security structure of the platform. The video also emphasizes the importance of networking security.
00:00:00 In this video, you'll learn about the importance of data reliability and performance on the Databricks Lakehouse platform. It addresses the limitations of data Lakes and introduces Delta Lake and photon as foundational technologies to enhance reliability, performance, and data management capabilities.
🔑 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.
00:04:12 This video provides an introduction to the Databricks Lakehouse Platform Architecture and Security. It explains the benefits of using the platform and introduces Photon, the next-generation query engine. The video also discusses the importance of having a unified governance and security structure.
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.
00:08:22 Introduction to Databricks Lakehouse Platform Architecture and Security. Databricks offers the Unity catalog for unified governance, Delta sharing for secure data sharing, and a divided architecture for simplified permissions. Unity catalog provides fine-grained access control, centralized governance, and detailed audit trails.
🔑 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.
00:12:31 The video introduces the Databricks Lakehouse Platform Architecture and Security. It discusses the challenges of data sharing and the limitations of existing technologies. Databricks developed Delta sharing as an open-source solution to securely share live data from the Lakehouse to any computing platform. The video also highlights the benefits of Delta sharing, including cross-platform compatibility, centralized administration and governance, and data reliability. The security structure of the Databricks Lakehouse Platform is explained, with a separate control plane and data plane. The data plane ensures data security within the customer's own cloud account. The video emphasizes the importance of networking security in the Databricks Lakehouse platform.
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.
00:16:41 This video introduces the architecture and security features of Databricks Lakehouse platform, including network boundaries, cluster management, access control, encryption, and compliance standards.
🔒 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.
00:20:51 This video provides an introduction to the Databricks Lakehouse platform architecture and security. It highlights the benefits of using serverless compute, managed by Databricks, which reduces costs and increases productivity. It also explains the key elements of Unity Catalog for data management in Databricks.
🔑 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.
00:25:02 Introduction to Databricks Lakehouse Platform Architecture and Security: Learn about the three-level namespace, tables, views, user-defined functions, storage credentials, and Delta sharing in Databricks Unity Catalog.
🔑 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.
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