title: Difference between "Dataset" and "Inline" sources in Azure Data Factory dataflows?
body: <p>What is the difference between the two source types &quot;Dataset&quot; and &quot;Inline&quot; in Azure Data Factory Data flow source ? In which situation should I use one instead of the other ?</p>
  <p>I've read the <a href="https://docs.microsoft.com/en-us/azure/data-factory/data-flow-source" rel="nofollow noreferrer">official documentation</a> from Microsoft but I couldn't figure it out :</p>
  <blockquote>
  <p>When a format is supported for both inline and in a dataset object, there are benefits to both. Dataset objects are reusable entities that can be used in other data flows and activities such as Copy. These reusable entities are especially useful when you use a hardened schema. Datasets aren't based in Spark. Occasionally, you might need to override certain settings or schema projection in the source transformation.</p>
  </blockquote>
  <blockquote>
  <p>Inline datasets are recommended when you use flexible schemas, one-off source instances, or parameterized sources. If your source is heavily parameterized, inline datasets allow you to not create a &quot;dummy&quot; object. Inline datasets are based in Spark, and their properties are native to data flow.</p>
  </blockquote>