Delta Lake is best described as what in relation to Spark?

• A. A relational storage layer for Spark that supports tables based on Parquet files.
• B. A Spark API for exporting data from a relational database into CSV files.
• C. A synchronization solution that replicates data between SQL Server and SPark.
• D. An in-memory cache for Spark dataframes.

Answer: (A)

Delta Lake is best described as a storage layer for Spark that sits on top of your data lake and uses Parquet files to store data, while adding table-like semantics with ACID transactions, schema enforcement, and time travel. It gives Spark a reliable, transactional view over data in the lake, so you can create Delta tables, run Spark SQL queries, and rely on consistent reads and writes across concurrent jobs. It’s not a data export API, a data replication system, or an in-memory cache; it’s the layer that makes lake data behave more like well-managed tables for analytic workloads.