What is the ideal data type to use when storing latitude / longitude in a MySQL database?

Basically it depends on the precision you need for your locations. Using DOUBLE you'll have a 3.5nm precision. DECIMAL(8,6)/(9,6) goes down to 16cm. FLOAT is 1.7m...

This very interesting table has a more complete list: http://mysql.rjweb.org/doc.php/latlng :

Datatype               Bytes            Resolution

Deg*100 (SMALLINT)     4      1570 m    1.0 mi  Cities
DECIMAL(4,2)/(5,2)     5      1570 m    1.0 mi  Cities
SMALLINT scaled        4       682 m    0.4 mi  Cities
Deg*10000 (MEDIUMINT)  6        16 m     52 ft  Houses/Businesses
DECIMAL(6,4)/(7,4)     7        16 m     52 ft  Houses/Businesses
MEDIUMINT scaled       6       2.7 m    8.8 ft
FLOAT                  8       1.7 m    5.6 ft
DECIMAL(8,6)/(9,6)     9        16cm    1/2 ft  Friends in a mall
Deg*10000000 (INT)     8        16mm    5/8 in  Marbles
DOUBLE                16       3.5nm     ...    Fleas on a dog

Hope this helps.

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Use MySQL's spatial extensions with GIS.

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Google provides a start to finish PHP/MySQL solution for an example "Store Locator" application with Google Maps. In this example, they store the lat/lng values as "Float" with a length of "10,6"

http://code.google.com/apis/maps/articles/phpsqlsearch.html

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MySQL's Spatial Extensions are the best option because you have the full list of spatial operators and indices at your disposal. A spatial index will allow you to perform distance-based calculations very quickly. Please keep in mind that as of 6.0, the Spatial Extension is still incomplete. I am not putting down MySQL Spatial, only letting you know of the pitfalls before you get too far along on this.

If you are dealing strictly with points and only the DISTANCE function, this is fine. If you need to do any calculations with Polygons, Lines, or Buffered-Points, the spatial operators do not provide exact results unless you use the "relate" operator. See the warning at the top of 21.5.6. Relationships such as contains, within, or intersects are using the MBR, not the exact geometry shape (i.e. an Ellipse is treated like a Rectangle).

Also, the distances in MySQL Spatial are in the same units as your first geometry. This means if you're using Decimal Degrees, then your distance measurements are in Decimal Degrees. This will make it very difficult to get exact results as you get furthur from the equator.

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When I did this for a navigation database built from ARINC424 I did a fair amount of testing and looking back at the code, I used a DECIMAL(18,12) (Actually a NUMERIC(18,12) because it was firebird).

Floats and doubles aren't as precise and may result in rounding errors which may be a very bad thing. I can't remember if I found any real data that had problems - but I'm fairly certain that the inability to store accurately in a float or a double could cause problems

The point is that when using degrees or radians we know the range of the values - and the fractional part needs the most digits.

The MySQL Spatial Extensions are a good alternative because they follow The OpenGIS Geometry Model. I didn't use them because I needed to keep my database portable.

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Depends on the precision that you require.

Datatype           Bytes       resolution
------------------ -----  --------------------------------
Deg*100 (SMALLINT)     4  1570 m    1.0 mi  Cities
DECIMAL(4,2)/(5,2)     5  1570 m    1.0 mi  Cities
SMALLINT scaled        4   682 m    0.4 mi  Cities
Deg*10000 (MEDIUMINT)  6    16 m     52 ft  Houses/Businesses
DECIMAL(6,4)/(7,4)     7    16 m     52 ft  Houses/Businesses
MEDIUMINT scaled       6   2.7 m    8.8 ft
FLOAT                  8   1.7 m    5.6 ft
DECIMAL(8,6)/(9,6)     9    16cm    1/2 ft  Friends in a mall
Deg*10000000 (INT)     8    16mm    5/8 in  Marbles
DOUBLE                16   3.5nm     ...    Fleas on a dog

From: http://mysql.rjweb.org/doc.php/latlng

To summarise:

The most precise available option is DOUBLE.

The most common seen type used is DECIMAL(8,6)/(9,6).

As of MySQL 5.7, consider using Spatial Data Types (SDT), specifically POINT for storing a single coordinate. Prior to 5.7, SDT does not support indexes (with exception of 5.6 when table type is MyISAM).

Note:

When using POINT class, the order of the arguments for storing coordinates must be POINT(latitude, longitude).

There is a special syntax for creating a spatial index.

The biggest benefit of using SDT is that you have access to Spatial Analyses Functions, e.g. calculating distance between two points (ST_Distance) and determining whether one point is contained within another area (ST_Contains).

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Based on this wiki article http://en.wikipedia.org/wiki/Decimal_degrees#Accuracy the appropriate data type in MySQL is Decimal(9,6) for storing the longitude and latitude in separate fields.

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Use DECIMAL(8,6) for latitude (90 to -90 degrees) and DECIMAL(9,6) for longitude (180 to -180 degrees). 6 decimal places is fine for most applications. Both should be "signed" to allow for negative values.

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No need to go far, according to Google Maps, the best is FLOAT(10,6) for lat and lng.

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We store latitude/longitude X 1,000,000 in our oracle database as NUMBERS to avoid round off errors with doubles.

Given that latitude/longitude to the 6th decimal place was 10 cm accuracy that was all we needed. Many other databases also store lat/long to the 6th decimal place.

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In a completely different and simpler perspective:

if you are relying on Google for showing your maps, markers, polygons, whatever, then let the calculations be done by Google!

you save resources on your server and you simply store the latitude and longitude together as a single string (VARCHAR), E.g.: "-0000.0000001,-0000.000000000000001" (35 length and if a number has more than 7 decimal digits then it gets rounded);

if Google returns more than 7 decimal digits per number, you can get that data stored in your string anyway, just in case you want to detect some flees or microbes in the future;

you can use their distance matrix or their geometry library for calculating distances or detecting points in certain areas with calls as simple as this: google.maps.geometry.poly.containsLocation(latLng, bermudaTrianglePolygon))

there are plenty of "server-side" APIs you can use (in Python, Ruby on Rails, PHP, CodeIgniter, Laravel, Yii, Zend Framework, etc.) that use Google Maps API.

This way you don't need to worry about indexing numbers and all the other problems associated with data types that may screw up your coordinates.

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TL;DR

Use FLOAT(8,5) if you're not working in NASA / military and not making aircrafts navi systems.

To answer your question fully, you'd need to consider several things:

Format

degrees minutes seconds: 40° 26′ 46″ N 79° 58′ 56″ W

degrees decimal minutes: 40° 26.767′ N 79° 58.933′ W

decimal degrees 1: 40.446° N 79.982° W

decimal degrees 2: -32.60875, 21.27812

Some other home-made format? Noone forbids you from making your own home-centric coordinates system and store it as heading and distance from your home. This could make sense for some specific problems you're working on.

So the first part of the answer would be - you can store the coordinates in the format your application uses to avoid constant conversions back and forth and make simpler SQL queries.

Most probably you use Google Maps or OSM to display your data, and GMaps are using "decimal degrees 2" format. So it will be easier to store coordinates in the same format.

Precision

Then, you'd like to define precision you need. Of course you can store coordinates like "-32.608697550570334,21.278081997935146", but have you ever cared about millimeters while navigation to the point? If you're not working in NASA and not doing satellites or rockets or planes trajectories, you should be fine with several meters accuracy.

Commonly used format is 5 digits after dots which gives you 50cm accuracy.

Example: there is 1cm distance between X,21.2780818 and X,21.2780819. So 7 digits after dot give you 1/2cm precision and 5 digits after dot will give you 1/2 meters precision (because minimal distance between distinct points is 1m, so rounding error cannot be more than half of it). For most civil purposes it should be enough.

degrees decimal minutes format (40° 26.767′ N 79° 58.933′ W) gives you exactly the same precision as 5 digits after dot

Space-efficient storage

If you've selected decimal format, then your coordinate is a pair (-32.60875, 21.27812). Obviously, 2 x (1 bit for sign, 2 digits for degrees and 5 digits for exponent) will be enough.

So here I'd like to support Alix Axel from comments saying that Google suggestion to store it in FLOAT(10,6) is really extra, because you don't need 4 digits for main part (since sign is separated and latitude is limited to 90 and longitude is limited to 180). You can easily use FLOAT(8,5) for 1/2m precision or FLOAT(9,6) for 50/2cm precision. Or you can even store lat and long in separated types, because FLOAT(7,5) is enough for lat. See MySQL float types reference. Any of them will be like normal FLOAT and equal to 4 bytes anyway.

Usually space is not an issue nowadays, but if you want to really optimize the storage for some reason (Disclaimer: don't do pre-optimization), you may compress lat(no more than 91 000 values + sign) + long(no more than 181 000 values + sign) to 21 bits which is significantly less than 2xFLOAT (8 bytes == 64 bits)

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While it isn't optimal for all operations, if you are making map tiles or working with large numbers of markers (dots) with only one projection (e.g. Mercator, like Google Maps and many other slippy maps frameworks expect), I have found what I call "Vast Coordinate System" to be really, really handy. Basically, you store x and y pixel coordinates at some way-zoomed-in -- I use zoom level 23. This has several benefits:

You do the expensive lat/lng to mercator pixel transformation once instead of every time you handle the point

Getting the tile coordinate from a record given a zoom level takes one right shift.

Getting the pixel coordinate from a record takes one right shift and one bitwise AND.

The shifts are so lightweight that it is practical to do them in SQL, which means you can do a DISTINCT to return only one record per pixel location, which will cut down on the number records returned by the backend, which means less processing on the front end.

I talked about all this in a recent blog post: http://blog.webfoot.com/2013/03/12/optimizing-map-tile-generation/

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depending on you application, i suggest using FLOAT(9,6)

spatial keys will give you more features, but in by production benchmarks the floats are much faster than the spatial keys. (0,01 VS 0,001 in AVG)

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MySQL uses double for all floats ... So use type double. Using float will lead to unpredictable rounded values in most situations

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Latitudes range from -90 to +90 (degrees), so DECIMAL(10, 8) is ok for that longitudes range from -180 to +180 (degrees) so you need DECIMAL(11, 8).

Note: The first number is the total number of digits stored, and the second is the number after the decimal point.

In short: lat DECIMAL(10, 8) NOT NULL, lng DECIMAL(11, 8) NOT NULL

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The spatial functions in PostGIS are much more functional (i.e. not constrained to BBOX operations) than those in the MySQL spatial functions. Check it out: link text

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I suggest you use Float datatype for SQL Server.

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The ideal datatype for storing Lat Long values is decimal(9,6)

This is at approximately 10cm precision, whilst only using 5 bytes of storage.

e.g. CAST(123.456789 as decimal(9,6))

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Lat Long calculations require precision, so use some type of decimal type and make the precision at least 2 higher than the number you will store in order to perform math calculations. I don't know about the my sql datatypes but in SQL server people often use float or real instead of decimal and get into trouble because these are are estimated numbers not real ones. So just make sure the data type you use is a true decimal type and not a floating decimal type and you should be fine.

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A FLOAT should give you all of the precision you need, and be better for comparison functions than storing each co-ordinate as a string or the like.

If your MySQL version is earlier than 5.0.3, you may need to take heed of certain floating point comparison errors however.

Prior to MySQL 5.0.3, DECIMAL columns store values with exact precision because they are represented as strings, but calculations on DECIMAL values are done using floating-point operations. As of 5.0.3, MySQL performs DECIMAL operations with a precision of 64 decimal digits, which should solve most common inaccuracy problems when it comes to DECIMAL columns

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