Key Concepts

Data Lakehouse

It is a modern data management system that combines the benefits of data lakes and data warehouses. It enables efficient data storage, processing, and analytics in a single architecture.

Delta Lake

It is a technology designed for building Lakehouse architectures.

Open-source storage framework with:

• ACID transactions for data reliability.
• Scalable metadata handling.
• Data versioning for historical tracking.
• Integrated with big data ecosystems like Apache Spark.
• Serves as the core technology for a Lakehouse architecture.

Unity Catalog

• Unified governance solution for data and AI assets on Azure Databricks.
• Provides centralized access control, auditing, lineage tracking, and data discovery across Databricks workspaces.
• Enables simplified security and governance for multi-cloud environments.
• Comparison: Unity Catalog focuses on data governance within Databricks, whereas AWS IAM is a broader identity and access management service.

Delta Table (Data Table Architecture)

• Default data table format in Azure Databricks.
• Optimized for data lakes, supporting:
• Streaming ingestion
• Batch processing
• Efficient querying and updates
• Provides schema enforcement, versioning, and optimized storage.

Delta Live Tables (Data Pipeline Framework)

• Proprietary framework in Azure Databricks.
• Designed to simplify ETL (Extract, Transform, Load) pipeline creation and management.

Features:

• Manages dependencies between datasets intelligently.
• Automatically deploys and scales infrastructure to maintain timely and accurate data processing.
• Optimized for real-time and batch data processing workflows.

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