Hey everyone! I’m working on a project where I need to convert MusicBrainz identifiers to their corresponding Spotify track IDs for musicians and records. The official Spotify API isn’t really helping me out here because I’m trying to process a massive dataset with thousands of MusicBrainz entries, and making individual API calls for each one is taking forever.
Has anyone dealt with this kind of bulk conversion before? I’m looking for a faster way to match MusicBrainz database entries with Spotify’s catalog without having to query their web API one by one. Any suggestions or alternative approaches would be really appreciated!
The current method is just too time-consuming for the scale I’m working with.
musicbrainz has bulk data exports u can download - way better than hitting their api. i matched them against spotify’s web player metadata using track duration plus artist name. it’s not perfect but catches most matches without the api hassle. got through 30k tracks in 2 days instead of weeks.
Had the same issue last year with a 50k+ track dataset. Instead of avoiding the APIs, I used request batching and caching - that’s what actually worked. Set up Redis to cache successful matches and added exponential backoff for rate limits. Here’s the game changer: pull ISRC codes from your MusicBrainz data first, then use those to match with Spotify. ISRCs are standardized, so you get way more reliable matches. Cut my processing time from weeks down to 3 days, with a 92% match rate that beat everything else I tried.
have you thought about using a script to automate some of it? i did that before and combined data from both APIs into one dataset. it’s way faster than hitting the API for each one. just a thought!
Hit this same problem with large music datasets. I built a local mapping database by batch downloading MusicBrainz dumps and scraping Spotify data through their API during off-peak hours. Then used fuzzy matching on artist names, album titles, and track names instead of hammering the APIs constantly. Got about 85% accuracy - not perfect but worked for what I needed. Also check out existing third-party databases that already handle cross-platform mappings. No point reinventing the wheel.
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