---
title: "Discussion on \"Building a Real-Time Data Mesh with RisingWave\" | Hashnode"
description: "Discussion on \"Building a Real-Time Data Mesh with RisingWave\". How streaming SQL turns domain-owned materialized views into self-serve, real-time data products."
url: "https://hashnode.com/posts/real-time-data-mesh-risingwave/6a10cb0dba30e4585696859c"
---

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Discussion

# [Building a Real-Time Data Mesh with RisingWave](https://risingwave.com/blog/real-time-data-mesh-risingwave?utm_source=hashnode&utm_medium=feed)

How streaming SQL turns domain-owned materialized views into self-serve, real-time data products.

May 22 · 9 min read · risingwave.com  
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-   [#data-mesh](https://hashnode.com/tag/data-mesh)
-   [#streaming-sql](https://hashnode.com/tag/streaming-sql)
-   [#data-architecture](https://hashnode.com/tag/data-architecture)
-   [#risingwave](https://hashnode.com/tag/risingwave)
-   [#kafka](https://hashnode.com/tag/kafka)

## 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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