How to store heightmap efficiently?

I store a game world (2D array of 5,000 x 5,000 int between -100 and 900) in an SQLite database:

CREATE TABLE map (x SMALLINT, y SMALLINT, h SMALLINT);

With VACCUM after INSERT it takes 500MB. I can compress (lzma) the file to 35-40MB but to use it I need to unzip. How do I store that so it could still run on a Raspberry Pi? A 2D array of int, or a list of 3-int tuples? Speed is not important but RAM and file size are.

Solution

I finally used the HDF5 file format, with pyTables. The outcome is a ~20MB file for the exact same data, directly usable by the application. Here is how I create it:

import tables

db_struct = {
    'x': tables.Int16Col(),
    'y': tables.Int16Col(),
    'h': tables.Int16Col()
}
h5file = tables.open_file("my_file.h5", mode="w", title='Map')
filters = tables.Filters(complevel=9, complib='lzo')
group = h5file.create_group('/', 'group', 'Group')
table = h5file.create_table(group, 'map', db_struct, filters=filters)
heights = table.row

for y in range(0, int(MAP_HEIGHT)):
    for x in range(0, int(MAP_WIDTH)):
        heights['x'] = x
        heights['y'] = y
        heights['h'] = h
        heights.append()
    table.flush()

table.flush()
h5file.close()