fast-geoip | memory replacement for geoip-lite , a node library

fast-geoip is a Python library. fast-geoip has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However fast-geoip build file is not available. You can download it from GitHub.

This library provides an interface to efficiently query MaxMind's GeoLite databases, which contain geolocation information for IPs. Concretely, this was created as an alternative to geoip-lite that adapts better to use-cases where either a low memory footprint is needed, not many IPs will be examined through the library or a high start-up overhead is unacceptable. Concretely, what geoip-lite does is that, on startup, it reads the whole database from disk, parses it and puts it all on memory, thus this results in the startup time being increased by about ~233 ms along with an increase of memory being used by the process of around ~110 MB, in exchange for any new queries being resolved with low sub-millisecond latencies (~0.02 ms). This works if you have a long-running process that will need to geolocate a lot of IPs and don't care about the increases in memory usage nor startup time, but if, for example, your use-case requires only geolocating a single IP, these trade-offs don't make much sense as only a small part of the satabase is needed to answer that query, not all of it. This library tries to provide a solution for these use-cases by separating the database into chunks and building an indexing tree around them, so that IP lookups only have to read the parts of the database that are needed for the query at hand. This results in the first query taking around 9ms and subsequent ones that hit the disk cache taking 0.7 ms, while memory consumption is kept at around 0.7MB. Wrapping it up, geoip-lite has huge overhead costs but sub-millisecond queries whereas this library doesn't have any overhead costs but its queries are slower (0.7-9 ms). And, without further addo, here's a code snippet of library usage (note that this library uses promises instead of synchronous functions, this is the only difference between this library and geoip-lite). Finally, to add some historical context, this library was originally built with the idea of using it for a lambda container that had to geolocate the IP of the current request, something that turned out to be impossible to do with geoip-lite because memory consumption exceeded the 126MB limit and it slowed down the lambda function by over 200ms just to query a single IP.