Highlight what is true about a Column Database.

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Question: Highlight what is true about a Column Database.

Option a) It is more suited for analytics than transactional data.
This statement aligns with the common understanding of columnar databases: they optimize read patterns for analytical queries and aggregations, rather than row-by-row transactional processing. The columnar storage enables fast scans of large datasets and efficient compression, which are beneficial for analytics.

Option b) It can store the same thing as a SQL database.
Columnar databases typically store relational data and can support SQL-like querying, so they can hold the same kinds of information as a traditional SQL database. The key distinction is mainly the storage format and access patterns, not the fundamental data types or capability to store similar data.

Option c) Adding a new feature will be easier than with a SQL database.
This claim is usually inaccurate. Schema evolution in columnar databases can be more complex or costly, depending on the implementation and the workload. While some systems support adding columns, other aspects of changing features (like indexing, compression, or query engine changes) can be non-trivial and may not be easier than in a traditional SQL database.

Option d) The information within each column can have a different schema.
This is misleading. In columnar databases, each column has a defined data type and the table schema applies across all rows for that column. While different columns in the same table can have different data types (i.e., different schemas per column), the phrasing suggests per-column schema variation within a single column, which is not accurate

Highlight what is true about a Column Database.

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