You plan to use Fabric to store data. You need to create a data store that supports the following: - Writing data by using T-SQL - Multi-table transactions - Dynamic data masking Which type of data…

A KQL database is optimized for large-scale telemetry and log data analytics using Kusto Query Language (KQL) and does not primarily support T-SQL writing, multi-table transactions, or dynamic data masking as core features.

While a Lakehouse supports T-SQL for querying and some operations, its primary transactional layer is often focused on single-table operations via Delta Lake, and it does not inherently offer full multi-table ACID transactions or dynamic data masking in the same way a dedicated relational warehouse does.

A Fabric Warehouse offers full T-SQL support for data writing, provides comprehensive ACID multi-table transaction capabilities, and natively supports advanced security features like Dynamic Data Masking, perfectly aligning with all specified requirements for a robust relational data store.

A semantic model is used for data modeling and reporting, providing a structured view over data for analytics, but it is not a data storage mechanism that supports T-SQL writing, transactions, or dynamic data masking.