MusicBrainz has very restrictive rate limits (1 per second max), so many of our calls to their API are returning errors, since we fetch TopMusic metadata en masse:
[WDHMBT]{"error": "Your requests are exceeding the allowable rate limit. Please see http://wiki.musicbrainz.org/XMLWebService for more information."}
I successfully deployed a custom clone of the MusicBrainz database to Heroku for a recent NodeJS project (https://github.com/scjohnson16/mb-server), so this may be an option. It's technically possible to fit the entire Releases table into the memory limit of a free Heroku deployment, but then we'll be restricted to a static database which is not ideal for new releases.
The only other option I see is to schedule requests at one second intervals, though this is also pretty unrealistic for a real-time case. Otherwise we'll have to simply limit ourselves to Spotify metadata.
MusicBrainz has very restrictive rate limits (1 per second max), so many of our calls to their API are returning errors, since we fetch TopMusic metadata en masse:
[WDHMBT]{"error": "Your requests are exceeding the allowable rate limit. Please see http://wiki.musicbrainz.org/XMLWebService for more information."}I successfully deployed a custom clone of the MusicBrainz database to Heroku for a recent NodeJS project (https://github.com/scjohnson16/mb-server), so this may be an option. It's technically possible to fit the entire Releases table into the memory limit of a free Heroku deployment, but then we'll be restricted to a static database which is not ideal for new releases.
The only other option I see is to schedule requests at one second intervals, though this is also pretty unrealistic for a real-time case. Otherwise we'll have to simply limit ourselves to Spotify metadata.