Which setting must be configured for the storage type of a large database table to optimize access performance?

When optimizing access performance for a large database table, configuring the storage type to Column Store is particularly advantageous. Column Store organizes data into columns rather than rows, which can lead to significant performance improvements, especially in analytical querying and scenarios involving large datasets.

Columnar storage is especially effective for performing operations such as aggregations and searches across a large volume of records, as it allows the database to read only the relevant columns needed for a query rather than entire rows. This reduces the amount of data that needs to be loaded into memory, thereby speeding up the access times for analytical and reporting tasks.

Additionally, Column Store storage is optimized for compression, which helps in reducing the overall storage footprint. This compression not only saves space but also enhances performance since less data needs to be read from disk.

Configuring a database table as a Row Store is typically more suitable for transactional workloads where operations often deal with entire records, making it less ideal for optimizing access performance in contexts where analytical queries are predominant.