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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May 22 · 9 min read · Most embedding pipelines are quietly stale. The model is fresh, the vector index is fast, but the embeddings themselves were written hours ago by a batch job that ran at 3 a.m. By the time a user type
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May 22 · 11 min read · RisingWave has always had a split personality. One half of the system is a streaming engine: incremental operators, state stores, barriers, materialized views that keep themselves correct as events ar
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May 22 · 10 min read · TL;DR: Real-time ML inference is rarely about the model. The hard part is computing features fast enough, getting them to the scoring service, and routing predictions back into your application. Risin
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