<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Using multiple clouds in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/using-multiple-clouds/m-p/25128#M17435</link>
    <description>&lt;P&gt;Are there recommendations and/or examples of leveraging AWS and Azure with Databricks? If so, is there any best practices to follow? Want to ensure we avoid expensive data transfer across clouds &lt;/P&gt;</description>
    <pubDate>Fri, 11 Jun 2021 02:27:19 GMT</pubDate>
    <dc:creator>Anonymous</dc:creator>
    <dc:date>2021-06-11T02:27:19Z</dc:date>
    <item>
      <title>Using multiple clouds</title>
      <link>https://community.databricks.com/t5/data-engineering/using-multiple-clouds/m-p/25128#M17435</link>
      <description>&lt;P&gt;Are there recommendations and/or examples of leveraging AWS and Azure with Databricks? If so, is there any best practices to follow? Want to ensure we avoid expensive data transfer across clouds &lt;/P&gt;</description>
      <pubDate>Fri, 11 Jun 2021 02:27:19 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/using-multiple-clouds/m-p/25128#M17435</guid>
      <dc:creator>Anonymous</dc:creator>
      <dc:date>2021-06-11T02:27:19Z</dc:date>
    </item>
  </channel>
</rss>

