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    <title>topic Re: Connect to Salesforce in Administration &amp; Architecture</title>
    <link>https://community.databricks.com/t5/administration-architecture/connect-to-salesforce/m-p/55822#M709</link>
    <description>&lt;P&gt;There is no "databricks" connector like the on you have in Unity Fedarating e.g. for Snowflake.&lt;BR /&gt;&lt;BR /&gt;You can use partner ecosystem e.g. Fivetran&amp;nbsp;&lt;BR /&gt;&lt;A href="https://www.fivetran.com/connectors/salesforce" target="_blank"&gt;https://www.fivetran.com/connectors/salesforce&lt;/A&gt;&lt;/P&gt;&lt;P&gt;to integrate Salesforce data to your Lakehouse.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;You also have spark salesforce library avaliable there:&lt;/P&gt;&lt;P&gt;&lt;A href="https://github.com/springml/spark-salesforce" target="_blank"&gt;https://github.com/springml/spark-salesforce&lt;/A&gt;&lt;/P&gt;&lt;P&gt;If you import this library, you can do :&lt;/P&gt;&lt;LI-CODE lang="python"&gt;spark.
                read.
                format("com.springml.spark.salesforce").
                option("username", "your_salesforce_username").
                option("password", "your_salesforce_password_with_secutiry_token"). //&amp;lt;salesforce login password&amp;gt;&amp;lt;security token&amp;gt;
                option("saql", saql)
                option("inferSchema", "true").
                load()&lt;/LI-CODE&gt;</description>
    <pubDate>Wed, 27 Dec 2023 16:22:35 GMT</pubDate>
    <dc:creator>Wojciech_BUK</dc:creator>
    <dc:date>2023-12-27T16:22:35Z</dc:date>
    <item>
      <title>Connect to Salesforce</title>
      <link>https://community.databricks.com/t5/administration-architecture/connect-to-salesforce/m-p/55821#M708</link>
      <description>&lt;P&gt;Curious if there's a Databricks connector for Salesforce on AWS?&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 27 Dec 2023 16:17:43 GMT</pubDate>
      <guid>https://community.databricks.com/t5/administration-architecture/connect-to-salesforce/m-p/55821#M708</guid>
      <dc:creator>leelee3000</dc:creator>
      <dc:date>2023-12-27T16:17:43Z</dc:date>
    </item>
    <item>
      <title>Re: Connect to Salesforce</title>
      <link>https://community.databricks.com/t5/administration-architecture/connect-to-salesforce/m-p/55822#M709</link>
      <description>&lt;P&gt;There is no "databricks" connector like the on you have in Unity Fedarating e.g. for Snowflake.&lt;BR /&gt;&lt;BR /&gt;You can use partner ecosystem e.g. Fivetran&amp;nbsp;&lt;BR /&gt;&lt;A href="https://www.fivetran.com/connectors/salesforce" target="_blank"&gt;https://www.fivetran.com/connectors/salesforce&lt;/A&gt;&lt;/P&gt;&lt;P&gt;to integrate Salesforce data to your Lakehouse.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;You also have spark salesforce library avaliable there:&lt;/P&gt;&lt;P&gt;&lt;A href="https://github.com/springml/spark-salesforce" target="_blank"&gt;https://github.com/springml/spark-salesforce&lt;/A&gt;&lt;/P&gt;&lt;P&gt;If you import this library, you can do :&lt;/P&gt;&lt;LI-CODE lang="python"&gt;spark.
                read.
                format("com.springml.spark.salesforce").
                option("username", "your_salesforce_username").
                option("password", "your_salesforce_password_with_secutiry_token"). //&amp;lt;salesforce login password&amp;gt;&amp;lt;security token&amp;gt;
                option("saql", saql)
                option("inferSchema", "true").
                load()&lt;/LI-CODE&gt;</description>
      <pubDate>Wed, 27 Dec 2023 16:22:35 GMT</pubDate>
      <guid>https://community.databricks.com/t5/administration-architecture/connect-to-salesforce/m-p/55822#M709</guid>
      <dc:creator>Wojciech_BUK</dc:creator>
      <dc:date>2023-12-27T16:22:35Z</dc:date>
    </item>
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