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    <title>topic Announcement | Introducing Lakehouse//RT: Real-Time Performance on a Unified Lakehouse in Announcements</title>
    <link>https://community.databricks.com/t5/announcements/announcement-introducing-lakehouse-rt-real-time-performance-on-a/m-p/160247#M874</link>
    <description>&lt;P&gt;&lt;SPAN&gt;Databricks has introduced &lt;/SPAN&gt;&lt;STRONG&gt;Lakehouse//RT&lt;/STRONG&gt;&lt;SPAN&gt;, a new real-time warehouse that brings millisecond performance directly to your lakehouse data, so teams can support operational analytics, BI, and app-serving workloads without moving data into a separate serving layer.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;Key highlights&lt;/STRONG&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Real-time speed on lakehouse data&lt;/STRONG&gt;&lt;SPAN&gt;: Lakehouse//RT is built for millisecond responsiveness on high-concurrency workloads, directly from existing lakehouse tables.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;No separate serving stack&lt;/STRONG&gt;&lt;SPAN&gt;: It removes the need for extra data copies, side systems, and additional pipelines for low-latency serving.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;One governed platform&lt;/STRONG&gt;&lt;SPAN&gt;: Real-time workloads stay on the same platform with Unity Catalog governance, helping teams keep access, lineage, and business logic consistent.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Built for live operational use cases&lt;/STRONG&gt;&lt;SPAN&gt;: Lakehouse//RT is designed for operational analytics, app serving, and BI serving where fast answers and high concurrency matter.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Open and simplified by design&lt;/STRONG&gt;&lt;SPAN&gt;: It runs on open table formats and is positioned as a simpler way to get real-time performance without introducing more architectural sprawl.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;&lt;SPAN&gt;In the full post, you’ll see how Databricks is bringing real-time responsiveness into the lakehouse itself, so organizations can support faster dashboards, applications, and operational decisions on live governed data, all on one platform.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/blog/introducing-lakehousert-real-time-performance-unified-lakehouse" target="_blank" rel="noopener"&gt; &lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_right:"&gt;👉&lt;/span&gt; Read the full post here &lt;/A&gt;&lt;/P&gt;</description>
    <pubDate>Tue, 23 Jun 2026 12:25:44 GMT</pubDate>
    <dc:creator>Tushar_Parekar</dc:creator>
    <dc:date>2026-06-23T12:25:44Z</dc:date>
    <item>
      <title>Announcement | Introducing Lakehouse//RT: Real-Time Performance on a Unified Lakehouse</title>
      <link>https://community.databricks.com/t5/announcements/announcement-introducing-lakehouse-rt-real-time-performance-on-a/m-p/160247#M874</link>
      <description>&lt;P&gt;&lt;SPAN&gt;Databricks has introduced &lt;/SPAN&gt;&lt;STRONG&gt;Lakehouse//RT&lt;/STRONG&gt;&lt;SPAN&gt;, a new real-time warehouse that brings millisecond performance directly to your lakehouse data, so teams can support operational analytics, BI, and app-serving workloads without moving data into a separate serving layer.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;Key highlights&lt;/STRONG&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Real-time speed on lakehouse data&lt;/STRONG&gt;&lt;SPAN&gt;: Lakehouse//RT is built for millisecond responsiveness on high-concurrency workloads, directly from existing lakehouse tables.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;No separate serving stack&lt;/STRONG&gt;&lt;SPAN&gt;: It removes the need for extra data copies, side systems, and additional pipelines for low-latency serving.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;One governed platform&lt;/STRONG&gt;&lt;SPAN&gt;: Real-time workloads stay on the same platform with Unity Catalog governance, helping teams keep access, lineage, and business logic consistent.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Built for live operational use cases&lt;/STRONG&gt;&lt;SPAN&gt;: Lakehouse//RT is designed for operational analytics, app serving, and BI serving where fast answers and high concurrency matter.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Open and simplified by design&lt;/STRONG&gt;&lt;SPAN&gt;: It runs on open table formats and is positioned as a simpler way to get real-time performance without introducing more architectural sprawl.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;&lt;SPAN&gt;In the full post, you’ll see how Databricks is bringing real-time responsiveness into the lakehouse itself, so organizations can support faster dashboards, applications, and operational decisions on live governed data, all on one platform.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/blog/introducing-lakehousert-real-time-performance-unified-lakehouse" target="_blank" rel="noopener"&gt; &lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_right:"&gt;👉&lt;/span&gt; Read the full post here &lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Tue, 23 Jun 2026 12:25:44 GMT</pubDate>
      <guid>https://community.databricks.com/t5/announcements/announcement-introducing-lakehouse-rt-real-time-performance-on-a/m-p/160247#M874</guid>
      <dc:creator>Tushar_Parekar</dc:creator>
      <dc:date>2026-06-23T12:25:44Z</dc:date>
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