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 text strings using locale-specific date formats (for example, "07/31/2025").
As separate character columns for year, month, and day that are concatenated when retrieved.
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?