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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12h ago · 8 min read · The scenario You've deployed a procurement agent. It monitors your SaaS subscriptions, finds unused seats, processes routine invoices under $5,000 automatically, and escalates larger ones for human review. In its first week it processed 143 transacti...
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17h ago · 12 min read · Feature engineering is where models are won and lost. It's also where ML teams waste enormous amounts of time arguing about tooling rather than building. The SQL vs. Python debate surfaces constantly, and most articles resolve it by quietly promoting...
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17h ago · 13 min read · The bid request lands in your DSP in 100 milliseconds. You have maybe 10ms of that window to pull features, run your bidding model, and return a price. Meanwhile, the audience segment powering your decision was built from yesterday's batch job. That ...
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17h ago · 12 min read · Credit decisions used to take days. A borrower submitted a paper application, a loan officer pulled a bureau report, an underwriter reviewed it overnight, and a letter arrived in the mail. Nobody questioned the timeline — it was just how lending work...
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17h ago · 11 min read · Feature backfilling is one of the most unglamorous problems in ML engineering — and one of the most consequential. When a model underperforms, the instinct is to improve the model. But more often, the fix requires better training data. And getting be...
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