<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Datasets on StorageNews</title><link>https://storagenews.top/tags/datasets/</link><description>Recent content in Datasets on StorageNews</description><generator>Hugo</generator><language>en</language><lastBuildDate>Wed, 11 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://storagenews.top/tags/datasets/index.xml" rel="self" type="application/rss+xml"/><item><title>Data storage sharding: Handle 750B points fast</title><link>https://storagenews.top/posts/data-storage-sharding-handle-750b-points-fast/</link><pubDate>Wed, 11 Mar 2026 00:00:00 +0000</pubDate><guid>https://storagenews.top/posts/data-storage-sharding-handle-750b-points-fast/</guid><description>&lt;meta charset="utf-8">
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&lt;p class="std-text">With AI training datasets exploding from 42 billion to over 750 billion points in just two years, naive storage architectures are now obsolete. Efficient management of &lt;strong>large datasets&lt;/strong> demands a shift from simple capacity expansion to rigorous architectural discipline involving &lt;strong>data partitioning&lt;/strong>, &lt;strong>compression&lt;/strong>, and strategic &lt;strong>lifecycle policies&lt;/strong>.&lt;/p></description></item><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></channel></rss>