The correct answer is A. Columnstore. According to CompTIA DataSys+, a columnstore index stores data in a column-oriented, tabular structure, where each column of a table is stored separately rather than storing entire rows together. This design is particularly optimized for analytical and reporting workloads, which commonly scan large datasets and perform aggregations on specific columns.
In a columnstore index, data is logically still represented in a table-like (tabular) format, but physically organized by columns instead of rows. This allows the database engine to read only the required columns for a query, significantly reducing disk I/O and improving query performance. DataSys+ highlights columnstore indexes as a best practice for data warehousing, business intelligence, and read-heavy analytical queries.
Option B, a non-clustered index, stores a separate index structure that contains indexed column values and pointers to the underlying table rows. While it improves lookup performance, it does not store data in a tabular columnar format. Option C, a unique index, is a constraint-based index that enforces uniqueness on column values but does not define how data is physically stored. Option D, a secondary index, is a general term for indexes that are not primary and does not specifically describe column-based tabular storage.
Sys+ emphasizes understanding different index types and their appropriate use cases. Columnstore indexes are distinct because they physically reorganize data by columns, compress data efficiently, and support high-performance analytics. This makes them especially effective in scenarios involving large datasets and complex queries.
Therefore, the index type that stores records in a tabular, column-oriented format is the columnstore index, making option A the correct and fully verified answer aligned with CompTIA DataSys+ objectives.
