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Storing Latitude & Longitude data as Floats or Decimal This is one of the most fundamental ways of storing geocoordinate data. Latitude & longitude values can be represented & stored in a SQL database using decimal points (Decimal degrees) rather than degrees (or Degrees Minutes Seconds).
Longitude has the range [-180;180] so it should be stored in DECIMAL(9,6) .
float(10,6) is just fine.
Any other convoluted storage schemes will require more translation in and out, and floating-point math is plenty fast.
I know you're asking about MySQL, but if spatial data is important to your business, you might want to reconsider. PostgreSQL + PostGIS are also free software, and they have a great reputation for managing spatial and geographic data efficiently. Many people use PostgreSQL only because of PostGIS.
I don't know much about the MySQL spatial system though, so perhaps it works well enough for your use-case.
The problem with using any other data type than "spatial" here is that your kind of "rectangular selection" can (usually, this depends on how bright your DBMS is - and MySQL certainly isn't generally the brightest) only be optimised in one single dimension.
The system can pick either the longitude index or the latitude index, and use that to reduce the set of rows to inspect. But after it has done that, there is a choice of : (a) fetching all found rows and scanning over those and test for the "other dimension", or (b) doing the similar process on the "other dimension" and then afterwards matching those two result sets to see which rows appear in both. This latter option may not be implemented as such in your particular DBMS engine.
Spatial indexes sort of do the latter "automatically", so I think it's safe to say that a spatial index will give the best performance in any case, but it may also be the case that it doesn't significantly outperform the other solutions, and that it's just not worth the bother. This depends on all sorts of things like the volume of and the distribution in your actual data etc. etc.
It is certainly true that float (tree) indexes are by necessity slower than integer indexes, because of the longer time it usually takes to execute '>' on floats than it does on integers. But I would be surprised if this effect were actually noticeable.
Google uses float(10,6) in their "Store locator" example. That's enough for me to go with that.
https://stackoverflow.com/a/5994082/1094271
Also, starting MySQL 5.6.x, spatial extensions support is much better and comparable to PostGIS in features and performance.
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