<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data Lakehouse on</title><link>https://dasarpai.github.io/tags/data-lakehouse/</link><description>Recent content in Data Lakehouse on</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>hari@dasarpai.com (Dr. Hari Thapliyaal)</managingEditor><webMaster>hari@dasarpai.com (Dr. Hari Thapliyaal)</webMaster><copyright>© 2026 Dr. Hari Thapliyaal</copyright><lastBuildDate>Wed, 25 Jan 2023 08:33:00 +0530</lastBuildDate><atom:link href="https://dasarpai.github.io/tags/data-lakehouse/index.xml" rel="self" type="application/rss+xml"/><item><title>Data Lake vs Data Warehouse vs Data Mart vs Lakehouse</title><link>https://dasarpai.github.io/dsblog/datalake-vs-data-warehouse/</link><pubDate>Wed, 25 Jan 2023 08:33:00 +0530</pubDate><author>hari@dasarpai.com (Dr. Hari Thapliyaal)</author><guid>https://dasarpai.github.io/dsblog/datalake-vs-data-warehouse/</guid><description>&lt;p>
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&lt;img class="my-0 rounded-md" loading="lazy" src="https://dasarpai.github.io/assets/images/dspost/dsp6040-Datalake-vs-Data-Warehouse.jpg" alt="Datalake vs Data Warehouse" />
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&lt;h1 class="relative group">What is the difference between Data Lake, Data Warehouse, Data Mart, and Lakehouse?
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&lt;h2 class="relative group">Introduction
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&lt;p>Enterprise data platforms have moved well beyond the simple lake-versus-warehouse debate. Today you will also hear about &lt;strong>data lakehouses&lt;/strong>, &lt;strong>data mesh&lt;/strong>, &lt;strong>data fabric&lt;/strong>, and layered designs such as the &lt;strong>medallion architecture&lt;/strong>. From a &lt;a href="https://dasarpai.github.io/dsblog/type-of-databases/">database perspective&lt;/a>, the core question is still the same: where does data live, how is it structured, and who can query it reliably?&lt;/p></description></item></channel></rss>