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Data as Service

• SAAS
• 定义数据源
• 定义输出
• 构造数据结构
• 构建计算策略与任务
• 可视化输出

• Pure Spark
• No need of coding, only declarative analytical workflows
• Data continuously streamed in & processed in near real-time
• Ready to use out-of-the-box
• Plug & play: flexible workflows (inputs, outputs, transformations, etc…)
• High performance and Fault Tolerance
• Scalable and High Availability
• Big Data OLAP on real-time to small data
• ETLs
• Triggers over streaming data
• Spark SQL language with streaming and batch data
• Kerberos and CAS compatible
• Visualization
• Microservice