Our Solutions_

Use Cases

Innovate your business with real-time stream
processing applications

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Using a stream processing platform


built for event-driven architectures


Event-driven processing is a programming paradigm focusing on responding to events or messages in real time. It is commonly used in systems that require real-time processing. The main advantage of this approach is that it allows the system to be more responsive and efficient since it can react immediately to events as they occur. Dealing with problem events faster than other companies or providing suggestions for preventative actions based on events as they happen provides a definite competitive edge.

Real-time and streaming analytics

Streaming analytics use cases include:

  • Check Icon Real-time stock trading
  • Check Icon Fraud detection
  • Check Icon Dynamically updating location information

RisingWave allows processing data while it is in motion to extract needed business value promptly and efficiently. It can gather data from various applications, sensors and devices, social media apps, websites, and more.

Processing the data in a continuous stream ensures that queries always return the most up-to-date information available.

Continuous monitoring and alerting

Monitoring and alerting use cases include:

  • Check Icon System monitoring to respond to failure concerns
  • Check Icon Security reporting to deal with potential threats
  • Check Icon Automating remedial actions based on possible errors

RisingWave helps to continuously monitor systems or applications to detect compliance and risk issues. Any anomalies can be detected quickly, so the response is swift and accurate. Together, monitoring and alerting provide a proactive approach to system management, allowing teams to identify and resolve issues before they escalate into full-blown crises.

Streaming ETL and data pipeline

Streaming and data pipeline use cases include:

  • Check Icon Internet of Things
  • Check Icon Fraud detection
  • Check Icon Real-time payment processing

RisingWave can easily build streaming data pipelines wherever the data originates and regardless of its intended destination. Some data sources include messaging queues, OLTP databases, or microservices, and data targets can be data warehouses or data lakes. The data will be in sync in seconds since the incoming data is processed incrementally rather than in batches.

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We appreciate your interest in RisingWave and will respond to your inquiry as soon as possible. In the meantime, feel free to explore our website for more information about our services and offerings.

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Welcome to RisingWave community

Get ready to embark on an exciting journey of growth and inspiration. Stay tuned for updates, exclusive content, and opportunities to connect with like-minded individuals.