Decimal or Float for High-Precision Latitude and Longitude Storage in SQL Server?

Understanding Decimal vs. Float for Double Precision in SQL Server

When attempting to store double precision values in SQL Server, developers may be confronted with the absence of an explicit "double" datatype. To resolve this dilemma, it's crucial to evaluate the nuances between two potential options: decimal and float.

Decimal vs. Float

Decimal is a precise datatype designed to represent exact decimal values. It utilizes a fixed-length binary storage format, ensuring the accuracy of calculations. In contrast, float is an approximate datatype that adheres to the IEEE 754 binary floating-point format. While float offers a wider range and can represent very small or large values, it may not always guarantee absolute precision.

Which to Choose for Latitude and Longitude Storage

Latitude and longitude values typically require high precision. For optimal accuracy, float should be selected as it provides a wider range and better accommodates decimal places, enabling representation of up to 5 digits after the decimal point. This precision aligns with the desired one-meter precision for latitude and longitude coordinates.

Other Considerations

• Real: An older datatype that is equivalent to float(24), offering reduced precision compared to float(53).
• Float(53): Equivalent to float(53) and represents the standard float datatype in SQL Server.
• Decimal(x, y): A datatype that specifies the precision (x) and scale (y) of decimal values. In this context, decimal(8,5) would be suitable for representing latitude and longitude values.

Recommendation for Latitude and Longitude Storage

Based on the need for high precision, float is the most appropriate datatype for storing latitude and longitude values in SQL Server. It provides the necessary range and precision to accurately represent the desired one-meter precision.

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