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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