In most relational database systems, how are DATE (and other date/time) values typically stored internally so that the database engine can sort and perform arithmetic efficiently?
As compressed JSON objects containing year, month, and day keys.
As separate character columns for year, month, and day that are concatenated when retrieved.
As text strings using locale-specific date formats (for example, "07/31/2025").
As a numeric offset (integer or fractional) from a fixed reference point-such as days or microseconds since an epoch date.
DATE and DATETIME types are normally stored in a compact numeric form (such as an integer counting days since a reference date, or microseconds since an epoch). Because the stored value is numeric, comparisons, indexing, and arithmetic can be performed rapidly. Storing dates as locale-dependent text strings would require conversions for every comparison and be error-prone; similarly, breaking the date into separate character fields or complex objects would add storage overhead and complicate indexes. Therefore, the numeric-offset representation is preferred in nearly all mainstream relational databases.
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What does it mean when we say date values are kept in a specialized structure?
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How do date values improve querying and arithmetic compared to text-based storage?
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Why is it incorrect to say date data types rely on text-based values?