Features

  • Stream Processing: True streaming model.
  • State Management: Robust state handling.
  • Scalability: Distributed and fault-tolerant.
  • Low Latency: Real-time data processing.

Benefits

  • Efficiency: Processes data as it arrives.
  • Reliability: Handles failures gracefully.
  • Scalability: Scales with data volume.
  • Flexibility: Supports complex event processing.

Use Cases

  • Real-time data analytics.
  • Event-driven applications.
  • Machine learning model scoring.
  • Monitoring and alerting systems.

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