You have a Fabric workspace. You have semi-structured data. You need to read the data by using T-SQL, KQL, and Apache Spark. The data will only be written by using Spark. What should you use to store the data?
A lakehouse in Microsoft Fabric is a versatile storage option designed for semi-structured and unstructured data, combining the flexibility of a data lake with the structure of a data warehouse. It supports Apache Spark, T-SQL, and KQL queries, making it ideal for the requirements.
Why the other options are not suitable:
B. Eventhouse: Eventhouse is not a valid Microsoft Fabric storage option.
C. Datamart: A datamart is designed for structured data and primarily supports T-SQL, but not Spark or KQL.
D. Warehouse: A warehouse is optimized for structured data and supports T-SQL, but it is not designed for semi-structured data or Spark.
A lakehouse is the best choice for storing data in a format that allows Spark to write it while enabling T-SQL and KQL for querying.
The eventhouse is the only one out of the four options that allows the creation of a KQL Database, therefore it is the only option that fully meets the criteria (being able to read the date via KQL, T-SQL and Spark).
Semi structured data should be stored in a lakehouse
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