Filtering on GeoJSON data - gis

Question

I was wondering how filtering is normally done on a FeatureCollection for GeoJSON data. For example, take the following earthquake data:
{
"type": "FeatureCollection",
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
"features": [
{ "type": "Feature", "properties": { "id": "ak16994521", "mag": 2.3, "time": 1507425650893, "felt": null, "tsunami": 0 }, "geometry": { "type": "Point", "coordinates": [ -151.5129, 63.1016, 0.0 ] } },
{ "type": "Feature", "properties": { "id": "ak16994519", "mag": 1.7, "time": 1507425289659, "felt": null, "tsunami": 0 }, "geometry": { "type": "Point", "coordinates": [ -150.4048, 63.1224, 105.5 ] } },
{ "type": "Feature", "properties": { "id": "ak16994517", "mag": 1.6, "time": 1507424832518, "felt": null, "tsunami": 0 }, "geometry": { "type": "Point", "coordinates": [ -151.3597, 63.0781, 0.0 ] } },
{ "type": "Feature", "properties": { "id": "ci38021336", "mag": 1.42, "time": 1507423898710, "felt": null, "tsunami": 0 }, "geometry": { "type": "Point", "coordinates": [ -118.497, 34.299667, 7.64 ] } },
{ "type": "Feature", "properties": { "id": "hv61900626", "mag": 2.91, "time": 1504833891990, "felt": null, "tsunami": 0 }, "geometry": { "type": "Point", "coordinates": [ -155.011833, 19.399333, 2.609 ] } }
]
}
Now, if this data is all within a single FeatureCollection, how would anyone filter the data, for example to view earthquakes with magnitude > 2.5 ? It seems like when dealing with a FeatureCollection the first thing to do would be to extract each of the features into its own item: is that what is usually done, so that individual properties may be queried?

Answer 1

GeoJSON is a transfer format and as you have noticed any operation on it requires you to read and parse the whole file every time. If you plan to do anything with the data you should translate it into a more useful format which supports indexes. If you need to keep to a file based format then I recommend GeoPackage which is supported by the majority of modern GIS. Alternatively, you could use a spatially enabled database such as PostGIS.
In either case the easiest way to convert the data is to use ogr2ogr