---
title: "Discussion on \"Real-Time Recommendation Features with Streaming SQL: Ranking Signals, Engagement Scoring, and User Behavior\" | Hashnode"
description: "Discussion on \"Real-Time Recommendation Features with Streaming SQL: Ranking Signals, Engagement Scoring, and User Behavior\". Ranking signals, engagement scoring, and user behavior features that reflect the last few minutes, not last night"
url: "https://hashnode.com/posts/real-time-features-recommendation-ranking/69d452c6926200ed2ea647c8"
---

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# [Real-Time Recommendation Features with Streaming SQL: Ranking Signals, Engagement Scoring, and User Behavior](https://risingwave.com/blog/real-time-features-recommendation-ranking?utm_source=hashnode&utm_medium=feed)

Ranking signals, engagement scoring, and user behavior features that reflect the last few minutes, not last night

Apr 7 · 18 min read · risingwave.com  
Updated Nov 8  
Read the article

-   [#feature-engineering](https://hashnode.com/tag/feature-engineering)
-   [#machine-learning](https://hashnode.com/tag/machine-learning)
-   [#ranking](https://hashnode.com/tag/ranking)
-   [#recommendations](https://hashnode.com/tag/recommendations)
-   [#streaming-sql](https://hashnode.com/tag/streaming-sql)

## Written by

[RisingWave Labs](https://hashnode.com/@RisingWaveLabs)

@RisingWaveLabs · Bay Area, California

  
[View profile](https://hashnode.com/@RisingWaveLabs)

RisingWave is an open-source real-time event streaming platform.

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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