What\'s the Best MySQL Data Type for Storing High-Precision Latitude/Longitude Data?

Optimizing MySQL Data Storage for Latitude/Longitude with High Precision

In the realm of geospatial data management, representing Latitude and Longitude with precision is crucial for accurate map calculations. This question explores the appropriate MySQL data type to store Latitude/Longitude values that extend to eight decimal places.

The Google document recommendation of FLOAT(10, 6) provides six decimal places of precision, falling short of the desired eight. To remedy this, consider employing FLOAT(10, 8), offering the necessary precision.

However, there exists an even more suitable option for geospatial data storage: MySQL's Spatial data types. Point, a single-value type, is specifically designed for representing geographical coordinates. It automatically handles the complexities of spatial indexing and calculation.

An example of using Point with MySQL:

CREATE TABLE `buildings` (
  `coordinate` POINT NOT NULL,
  SPATIAL INDEX `SPATIAL` (`coordinate`)
) ENGINE=InnoDB;

INSERT INTO `buildings` (`coordinate`) VALUES (POINT(40.71727401 -74.00898606));

By utilizing Point, MySQL ensures precision, efficient spatial indexing, and optimized map calculations.

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