Data warehouses evolved from specialized on-premises systems into simpler, but highly scalable, data appliances, then into the cloud. Data and analytics technical professionals will find the cloud variants suitable for most organizations. We evaluate cloud-based warehouses from Amazon and Microsoft.
- Management of Large Volumes of Data
- Amazon Redshift Support for Large Volumes
- Microsoft Azure SQL Data Warehouse
- Continuous Data Loading
- Amazon Redshift and Continuous Loading
- Microsoft Azure SQL Data Warehouse and Continuous Loading
- Support for Queries on Multiple Data Types and Sources
- Amazon Redshift and Data Type Support
- Microsoft Azure SQL Data Warehouse and Data Type Support
- Support for Advanced Analytics Queries
- Amazon Redshift Support for Advanced Analytics
- Microsoft Azure SQL Data Warehouse Support for Advanced Analytics
- Support for Unstructured Data
- Amazon Redshift and Unstructured Data
- Microsoft Azure SQL Data Warehouse and Unstructured Data
- Support for Operational and Real-Time BI Queries
- Amazon Redshift and Operational and Real-Time BI Queries
- Microsoft Azure SQL Data Warehouse and Operational and Real-Time BI Queries
- System Availability
- Amazon Redshift System Availability
- Microsoft Azure SQL Data Warehouse System Availability
- Support for Users of Differing Types and Skills
- Amazon Redshift Support for Users of Differing Types and Skills
- Microsoft Azure SQL Data Warehouse Support for Users of Differing Types and Skills
- Administration and Management
- Amazon Redshift Administration and Management
- Microsoft Azure SQL Data Warehouse Administration and Management
- Use-Case Suitability
- Traditional Data Warehouse
- Operational and Real-Time Data Warehouse
- Context-Independent Data Warehouse
- Logical Data Warehouse
- Features and Capabilities
- General Remarks
- Support for SQL and Development
- Amazon Redshift Features and Capabilities
- Microsoft Azure SQL Data Warehouse Features and Capabilities
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