The document compares Kubernetes SQL Server with traditional RDBMS, highlighting its cloud-native capabilities, support for both batch and real-time processing, and automatic scaling based on workload. It discusses pricing models, data structure support, and emphasizes built-in machine learning and basic analytics features. Collaboration is noted as a strength in Kubernetes SQL Server, though it has more limited features compared to traditional systems.

1. Kubernetes

2. Kubernetes SQL Server Data Warehouse
Cloud-native, built on Spark Traditional RDBMS
Supports batch & real-time processing Primarily batch
Automatic scaling based on workload Manual scaling, less dynamic
Pay-as-you-go pricing Fixed licensing/hardware costs
Structure, semi-structured and unstructured data Primarily focused on structured data
Built-in ML support and notebook integration Basic analytics support
Real-time collaboration (shared notebooks) Limited collaboration features