The demos in this directory aim to demonstrate how to build a streaming data pipeline for real-world industry applications. All demos can be run using Docker Compose for ease of setup and include detailed deployment instructions.
Here are the runnable demos so far:
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Real-time energy grid monitoring: Monitor the energy consumption and production patterns of an energy grid in real-time using Kafka, PostgreSQL, RisingWave, and Grafana.
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Real-time flight tracking system: Keep track of live flight data from Aviationstack API using Kafka, RisingWave, and Metabase.
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Real-time monitoring, predictive maintenance, and anomaly detection: Detect anomalies in real-time for PBL86-80 motors using MQTT, RisingWave, and Grafana.
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Wikipedia edits monitoring system: Track contributions made to Wikipedia pages in real time using the Wikipedia API, Kafka, and RisingWave.
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Spoofing detection with actual Market data: Detect spoofing in trading events in real-time by leveraging RisingWave and real-time market data from Databento. Detailed explanations can be found in this blog post.
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Real-time PostgreSQL → Apache Iceberg CDC: Stream PostgreSQL CDC into Apache Iceberg with RisingWave’s native connectors, query it through Spark, Trino, or Dremio, then loop the results back for a faster, simpler stack than Kafka and/or Flink.
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Traffic flow monitoring and predication: Detect traffic flow by ingesting car speed events in real-time, and predict the traffic flow based historical data and a ML model.