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Azure Data Lake Storage
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. Stay Connected! If you enjoyed this post, don’t forget to follow me on social media for more updates and insights: Twitter: madhavganesan Instagram: madhavganesan LinkedIn: madhavganesan
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.
Stay Connected!
If you enjoyed this post, don’t forget to follow me on social media for more updates and insights:
Twitter: madhavganesan
Instagram: madhavganesan
LinkedIn: madhavganesan
