Open cw75 opened 7 months ago
RisingWave is well-suited for Streaming ETL, real-time analytics, and event-driven applications. These use cases leverage RisingWave's capabilities in continuous data processing, offering advantages like lower latency, scalability, and real-time insights for various industries (RisingWave use cases).
Would you like more detail on any specific use case?
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Thanks
Can you give me more details? @runllm
RisingWave supports three primary use cases: Streaming ETL, real-time analytics, and event-driven applications.
Streaming ETL: It involves continuous data extraction, transformation, and loading. RisingWave excels here by ingesting data from various sources, performing transformations (e.g., mapping, filtering, joining), and sinking data to downstream systems. This approach offers benefits like lower latency and better data freshness compared to batch ETL (RisingWave use cases).
Real-time Analytics: RisingWave enables analyzing data as it's generated, providing insights almost instantly. It supports this through real-time data ingestion and transformation, maintaining fresh results for direct query serving from dashboards, and allowing data sinking for further enrichment (RisingWave use cases).
Event-driven Applications: These applications react to events rather than requests. RisingWave facilitates this by allowing continuous event ingestion and processing, handling out-of-order events, maintaining state across events, and integrating with systems like Apache Kafka for event streaming and storage. This enables sophisticated, real-time interactions within applications (RisingWave use cases).
Would you like to explore any of these use cases further?
Sources:
This is an AI-generated answer and your feedback is appreciated! Please leave a 👍 if this is helpful and 👎 if it is not.
Mention @runllm to ask follow-up questions. See runllm.com for more!
What are the typical use cases for RisingWave?