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Super-powers for data scientists
- Create full data pipelines: ingestion, transformation, predictive modelling, aggregations and statistics
- Deliver streaming, interactive and batch workloads under the same "lambda" architecture
- Scale to petabytes: with no additional performance tuning required
- Integrate with machine learning innovations: currently includes MLLib, Vowpal Wabbit, Sparkling H2O, Python and R, et.al.
- Deploy on-premise or cloud: while remaining service-provider agnostic - no dependence on any single cloud managed service
- Deliver Enterprise class services: via high availability, resilience, security, interoperability, and ease of management