Stream Processing Services enable the real-time processing, analysis, and management of continuous data streams, supporting the ingestion, transformation, and enrichment of data as it flows through a data centric architecture. These services are designed to handle high-throughput data from diverse sources such as IoT devices, sensors, logs, and event-driven services, processing it in real-time or near-real-time to provide instant insights, triggers, or actions. Stream Processing Services are essential for use cases requiring real-time analytics, monitoring, and decision-making, such as fraud detection, predictive analytics, and operational monitoring. By processing data on-the-fly, these services eliminate the need for batch processing, enabling organizations to react to new information as it arrives, ensuring that valuable data is always up-to-date and accessible for critical applications. Key Features: * Real-Time Data Processing: Stream Processing Services are optimized for low-latency, continuous processing of data streams, allowing data to be ingested, analyzed, and acted upon in real time. * Scalability: These services are designed to handle high-volume, high-velocity data streams, scaling horizontally to accommodate large amounts of data while maintaining processing speed and performance. * Event-Driven Architecture: Stream Processing Services work in an event-driven architecture, processing data based on events or triggers, enabling actions to be taken immediately in response to specific conditions or patterns. * Data Enrichment: These services support the enrichment of incoming data streams, allowing raw data to be processed and made ready for analysis or use in downstream services and applications. * Fault Tolerance: Stream Processing Services are built with fault tolerance mechanisms to ensure continuous processing even in the event of failures, maintaining data integrity and system reliability. * Integration with Data Repositories: These services are often integrated with data repositories such as Data Lakes, enabling the seamless flow of processed data for storage, analysis, or further downstream processing. * Analytics and Monitoring: Stream Processing Services provide real-time monitoring and analytics capabilities to identify data trends, detect anomalies, and gain insights as the data flows through the system, empowering quick decision-making.