Comments (6)
RisingWave is well-suited for Streaming ETL, real-time analytics, and event-driven applications. These use cases leverage its capabilities for continuous data processing, offering advantages like lower latency, scalability, and real-time insights (RisingWave use cases).
Would you like more detail on any specific use case?
Sources:
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Thanks.
from test.
@RunLLM can you give me a bit more detail?
from test.
Streaming ETL in RisingWave involves continuous data extraction, transformation, and loading across systems with benefits such as low latency and high scalability. It supports data ingestion from various sources, enables complex transformations, and allows sinking processed data to downstream systems. Real-time analytics with RisingWave offers insights by analyzing data as it arrives, supporting direct queries from dashboards and integration with databases for enriched datasets. Event-driven applications benefit from RisingWave's continuous event ingestion and processing, handling out-of-order events, and maintaining state across events for sophisticated processing. These capabilities make RisingWave suitable for applications like IoT data processing, real-time ad performance analysis, and online recommendation systems (RisingWave use cases).
Would you like examples or further explanation on how RisingWave implements these use cases?
Sources:
from test.
@RunLLM thanks!
from test.
You're welcome! If you have any more questions or need further assistance, feel free to ask.
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