A company needs to analyze a large amount of data stored in its Hadoop cluster. Which of the following best describes the benefit of using Databricks SQL with a Hadoop cluster?

Question

Options

• ADatabricks SQL provides faster query processing than traditional Hadoop tools.
• BDatabricks SQL allows users to store and analyze data directly in Hadoop.
• CDatabricks SQL provides more advanced security features than Hadoop.
• DDatabricks SQL provides better support for unstructured data than Hadoop.

• A
  76% (50)
• B
  5% (3)
• C
  12% (8)
• D
  8% (5)

Explanation

Databricks SQL leverages Apache Spark under the hood, which processes data in-memory across distributed nodes - making it significantly faster than traditional Hadoop MapRedisk-based tools like Hive, which write intermediate results to disk. B is wrong because Databricks SQL doesn't store data in Hadoop; it connects to data sources (including HDFS or cloud storage) but uses its own compute engine. C is wrong because while Databricks has solid security features, that's not the defining benefit over Hadoop - Hadoop also has mature security via Kerberos and Ranger. D is wrong because Hadoop's HDFS actually handles unstructured data well, and Databricks SQL is primarily optimized for structured/semi-structured SQL workloads, not unstructured data.

Memory tip: Think "Databricks = Databricks = fast, solid foundation." Its core value proposition is speed - Spark's in-memory processing vs. Hadoop's slower disk-based MapReduce. When you see Databricks SQL in an exam question, the answer almost always points to performance.

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