RisingWave is a real-time event streaming platform designed to offer the simplest and most cost-effective way to process, analyze, and manage real-time event data — with built-in support for the Apache Iceberg™ open table format. It provides both a Postgres-compatible SQL interface and a DataFrame-style Python interface.
RisingWave can ingest millions of events per second, continuously join and analyze live streams with historical data, serve ad-hoc queries at low latency, and manage data reliably in Apache Iceberg™ tables.
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3d ago · 8 min read · sFlow's continuous wire-speed packet sampling lets RisingWave detect volumetric floods within seconds. By streaming sFlow records and HTTP access logs into Kafka, you can run SQL window aggregations directly on live traffic data, alerting on anomalou...
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3d ago · 9 min read · A SQL-based UEBA system computes rolling behavioral baselines for users and entities using window aggregations, then flags deviations in real time. Unlike ML-based UEBA, it requires no model training, no feature pipelines, and no retraining cycles. I...
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3d ago · 8 min read · SQL window aggregations detect brute force attacks by counting failed authentication attempts per account within a fixed time window, triggering alerts when the count exceeds a threshold. Credential stuffing is detected at the campaign level by aggre...
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3d ago · 8 min read · Detect lateral movement in real time by ingesting authentication logs from Kafka into RisingWave, then running a SQL materialized view that counts distinct destination hosts per source account inside a session window. When the count crosses a thresho...
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3d ago · 8 min read · You can build a streaming security audit trail by connecting RisingWave to PostgreSQL and MySQL CDC sources plus Kafka topics, enriching those events with SQL joins, and writing the results into Apache Iceberg tables on S3. Historical compliance quer...
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