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RisingWave enables real-time analytics on Apache Iceberg tables by continuously ingesting data from Kafka and databases into Iceberg via streaming sinks, and — in v2.8+ — directly querying Iceberg tables as sources. This means your dashboards and app...

A real-time data lakehouse with RisingWave and Apache Iceberg on S3 gives you sub-minute data freshness, full SQL analytics, and object storage costs — without a proprietary data warehouse. RisingWave streams data continuously into Iceberg tables on ...

A streaming lakehouse combines real-time stream processing with open-format data lake storage. RisingWave handles the streaming SQL layer — ingesting from Kafka and databases, applying continuous transformations — while Apache Iceberg provides ACID-c...

RisingWave enables real-time social media analytics by continuously aggregating post engagement, brand mention frequency, and hashtag trends from Kafka-sourced social event streams. Marketing teams can detect viral content, emerging sentiment shifts,...

Real-time leaderboards for games can be built with streaming SQL by ingesting score events from Kafka into RisingWave, then defining materialized views that continuously rank players. This approach delivers sub-second leaderboard updates at any scale...

A real-time customer 360 for banking with streaming SQL means maintaining a continuously updated unified customer profile—combining transactions, product holdings, service interactions, and risk signals—as a set of materialized views that any downstr...

Real-time P&L calculation means continuously computing profit and loss as trades execute and market prices move, rather than running batch jobs at end-of-day. With RisingWave's streaming SQL, trading desks can maintain live materialized views that ag...

Industrial monitoring platforms collect telemetry from thousands of devices simultaneously. You need two things at once: a real-time dashboard that tells you whether a device is behaving normally right now, and accurate historical reports that tell y...
