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    <title>topic Re: Deltalkake vs Delta table in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/deltalkake-vs-delta-table/m-p/5029#M1562</link>
    <description>&lt;P&gt;Delta Lake and Delta table are related concepts in the Apache Delta Lake project. which extends Apache Spark with ACID (Atomicity, Consistency, Isolation, Durability) capabilities for data lakes. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Delta Lake provides a storage layer that enables transactional and scalable data processing on top of cloud storage systems like Hadoop Distributed File System (HDFS)/Amazon S3/ADLS.&lt;/P&gt;&lt;P&gt;Reference: &lt;A href="https://docs.delta.io/latest/delta-intro.html" alt="https://docs.delta.io/latest/delta-intro.html" target="_blank"&gt;https://docs.delta.io/latest/delta-intro.html&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;A Delta table is a collection of data organized in a tabular format within Delta Lake. It represents a table structure with schema and associated data stored in a Delta Lake format. There are 2 types of delta tables&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;Managed table&lt;/LI&gt;&lt;LI&gt;Unmanaged table&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;Please refer to the following document for more information about managed and unmanaged delta tables:&lt;/P&gt;&lt;P&gt;&lt;A href="https://docs.databricks.com/lakehouse/data-objects.html#managed-table" alt="https://docs.databricks.com/lakehouse/data-objects.html#managed-table" target="_blank"&gt;https://docs.databricks.com/lakehouse/data-objects.html#managed-table&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Key features of Delta Lake and Delta tables are the same and they include:&lt;/P&gt;&lt;P&gt;ACID transactions&lt;/P&gt;&lt;P&gt;Schema enforcement and evolution&lt;/P&gt;&lt;P&gt;Time travel&lt;/P&gt;&lt;P&gt;Data reliability&lt;/P&gt;&lt;P&gt;Metadata management&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;In summary, Delta Lake is the underlying storage layer that provides transactional and reliability features, while Delta tables represent the tabular structures within Delta Lake, offering ACID properties, schema enforcement, versioning, and other Delta Lake capabilities. Delta tables are the primary means of working with structured data in Delta Lake.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;</description>
    <pubDate>Mon, 01 May 2023 15:23:28 GMT</pubDate>
    <dc:creator>Annapurna_Hiriy</dc:creator>
    <dc:date>2023-05-01T15:23:28Z</dc:date>
    <item>
      <title>Deltalkake vs Delta table</title>
      <link>https://community.databricks.com/t5/data-engineering/deltalkake-vs-delta-table/m-p/5027#M1560</link>
      <description>&lt;P&gt;Can somebody give me good definition of delta lake vs delta table? What are the use cases of each, similarities and differences? Sorry I’m new to databricks ans trying to learn.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Sat, 29 Apr 2023 15:12:01 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/deltalkake-vs-delta-table/m-p/5027#M1560</guid>
      <dc:creator>Krish1</dc:creator>
      <dc:date>2023-04-29T15:12:01Z</dc:date>
    </item>
    <item>
      <title>Re: Deltalkake vs Delta table</title>
      <link>https://community.databricks.com/t5/data-engineering/deltalkake-vs-delta-table/m-p/5028#M1561</link>
      <description>&lt;P&gt;Delta Lake is an open-source storage layer that is designed to bring reliability to data lakes. It is built on top of Apache Spark and provides features such as ACID transactions, schema enforcement, and time travel. Delta Lake is essentially a storage format that provides a set of features for managing data in a data lake environment.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Delta tables, on the other hand, are tables that are created using the Delta Lake storage format. Delta tables are optimized for use in data lake environments and provide features such as ACID transactions, schema enforcement, and time travel. Delta tables are essentially a specific type of table that is built on top of the Delta Lake storage format.&lt;/P&gt;&lt;P&gt;In summary, Delta Lake is a storage layer that provides features for managing data in a data lake environment, while Delta tables are tables that are built on top of the Delta Lake storage format and provide optimized features for working with data in a data lake environment.&lt;/P&gt;</description>
      <pubDate>Mon, 01 May 2023 10:50:50 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/deltalkake-vs-delta-table/m-p/5028#M1561</guid>
      <dc:creator>Rishabh-Pandey</dc:creator>
      <dc:date>2023-05-01T10:50:50Z</dc:date>
    </item>
    <item>
      <title>Re: Deltalkake vs Delta table</title>
      <link>https://community.databricks.com/t5/data-engineering/deltalkake-vs-delta-table/m-p/5029#M1562</link>
      <description>&lt;P&gt;Delta Lake and Delta table are related concepts in the Apache Delta Lake project. which extends Apache Spark with ACID (Atomicity, Consistency, Isolation, Durability) capabilities for data lakes. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Delta Lake provides a storage layer that enables transactional and scalable data processing on top of cloud storage systems like Hadoop Distributed File System (HDFS)/Amazon S3/ADLS.&lt;/P&gt;&lt;P&gt;Reference: &lt;A href="https://docs.delta.io/latest/delta-intro.html" alt="https://docs.delta.io/latest/delta-intro.html" target="_blank"&gt;https://docs.delta.io/latest/delta-intro.html&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;A Delta table is a collection of data organized in a tabular format within Delta Lake. It represents a table structure with schema and associated data stored in a Delta Lake format. There are 2 types of delta tables&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;Managed table&lt;/LI&gt;&lt;LI&gt;Unmanaged table&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;Please refer to the following document for more information about managed and unmanaged delta tables:&lt;/P&gt;&lt;P&gt;&lt;A href="https://docs.databricks.com/lakehouse/data-objects.html#managed-table" alt="https://docs.databricks.com/lakehouse/data-objects.html#managed-table" target="_blank"&gt;https://docs.databricks.com/lakehouse/data-objects.html#managed-table&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Key features of Delta Lake and Delta tables are the same and they include:&lt;/P&gt;&lt;P&gt;ACID transactions&lt;/P&gt;&lt;P&gt;Schema enforcement and evolution&lt;/P&gt;&lt;P&gt;Time travel&lt;/P&gt;&lt;P&gt;Data reliability&lt;/P&gt;&lt;P&gt;Metadata management&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;In summary, Delta Lake is the underlying storage layer that provides transactional and reliability features, while Delta tables represent the tabular structures within Delta Lake, offering ACID properties, schema enforcement, versioning, and other Delta Lake capabilities. Delta tables are the primary means of working with structured data in Delta Lake.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 01 May 2023 15:23:28 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/deltalkake-vs-delta-table/m-p/5029#M1562</guid>
      <dc:creator>Annapurna_Hiriy</dc:creator>
      <dc:date>2023-05-01T15:23:28Z</dc:date>
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