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    <title>topic Delta vs. Parquet in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/delta-vs-parquet/m-p/24756#M17233</link>
    <description>&lt;P&gt;I'm curious about the benefits of using the Delta file format vs. Parquet. Is there any downside to using Delta?&lt;/P&gt;</description>
    <pubDate>Mon, 14 Jun 2021 20:21:50 GMT</pubDate>
    <dc:creator>User16826992185</dc:creator>
    <dc:date>2021-06-14T20:21:50Z</dc:date>
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      <title>Delta vs. Parquet</title>
      <link>https://community.databricks.com/t5/data-engineering/delta-vs-parquet/m-p/24756#M17233</link>
      <description>&lt;P&gt;I'm curious about the benefits of using the Delta file format vs. Parquet. Is there any downside to using Delta?&lt;/P&gt;</description>
      <pubDate>Mon, 14 Jun 2021 20:21:50 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/delta-vs-parquet/m-p/24756#M17233</guid>
      <dc:creator>User16826992185</dc:creator>
      <dc:date>2021-06-14T20:21:50Z</dc:date>
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    <item>
      <title>Re: Delta vs. Parquet</title>
      <link>https://community.databricks.com/t5/data-engineering/delta-vs-parquet/m-p/24757#M17234</link>
      <description>&lt;P&gt;Not really. You get upsides like transactions, time travel, upsert/merge/deletes. There is some cost to that, as Delta manages that by writing and managing many smaller Parquet files and has to re-read them to recreate the current or past state of the data. VACUUMing the data set periodically takes time too. So you may incur a little runtime overhead for these reasons; then again, Delta offers advanced features like z-order indexing and data skipping with Spark that also make it faster to read than Parquet.&lt;/P&gt;</description>
      <pubDate>Thu, 17 Jun 2021 23:17:18 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/delta-vs-parquet/m-p/24757#M17234</guid>
      <dc:creator>sean_owen</dc:creator>
      <dc:date>2021-06-17T23:17:18Z</dc:date>
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