<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Minio on StorageNews</title><link>https://storagenews.top/tags/minio/</link><description>Recent content in Minio on StorageNews</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 09 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://storagenews.top/tags/minio/index.xml" rel="self" type="application/rss+xml"/><item><title>AIStor Table Sharing: Stop Moving Datasets to Databricks</title><link>https://storagenews.top/posts/aistor-table-sharing-stop-moving-datasets-to-databricks/</link><pubDate>Mon, 09 Mar 2026 00:00:00 +0000</pubDate><guid>https://storagenews.top/posts/aistor-table-sharing-stop-moving-datasets-to-databricks/</guid><description>&lt;meta charset="utf-8">
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&lt;p class="std-text">MinIO&amp;#039;s March 9, 2026 release eliminates the complex pipelines historically required to move on-premises data to Databricks. This update fundamentally shifts hybrid analytics by embedding &lt;strong>Delta Sharing&lt;/strong> directly into the object storage layer, removing the need for duplicate datasets or separate governance systems. By integrating this open protocol natively, organizations can finally address data sovereignty and performance constraints without sacrificing access to cloud-based AI tools.&lt;/p></description></item><item><title>MinIO + QBO Cloud: fixing AI storage bottlenecks</title><link>https://storagenews.top/posts/minio-qbo-cloud-fixing-ai-storage-bottlenecks/</link><pubDate>Fri, 27 Feb 2026 00:00:00 +0000</pubDate><guid>https://storagenews.top/posts/minio-qbo-cloud-fixing-ai-storage-bottlenecks/</guid><description>&lt;meta charset="utf-8">
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&lt;p class="std-text">The February 27, 2026 alliance between QBO Cloud and MinIO immediately addresses the bottleneck of &lt;strong>exascale data foundation&lt;/strong>. This partnership proves that &lt;strong>enterprise-grade object storage&lt;/strong> must evolve from simple archival silos into the primary engine driving modern AI infrastructure. The prevailing model of disjointed compute and storage layers is failing under the weight of generative workloads, necessitating a unified approach that merges bare-metal agility with high-performance data access.&lt;/p></description></item></channel></rss>