Of course there are alternatives to SongKong but there are some things mostly unique to SongKong and/or JThink.

  • SongKong has been developed over many years and is the successor to the first JThink tagger called Jaikoz, Jaikoz itself was the first commercial tagger to make use of the MusicBrainz Api, and I was also lead developer for the MusicBrainz search api for many years, so I have a very good understanding of the MusicBrainz database
  • Jaikoz was also the first tagger to make use of the Acoustid fingerprinting database, so we also have a long relationship with Acoustid and this had led to novel features such as the Acoustid Album database, that is unique to Jthink
  • And unlike other taggers we have our own dedicated server that combines MusicBrainz, Discogs and Acoustid for better and faster results
  • The only other tagger with a similar level of integration with MusicBrainz to SongKong and Jaikoz is MusicBrainz Picard. But because this is provided by MusicBrainz itself it is restricted in features by being too closely linked to MusicBrainz, and cannot make proper use of other sources such as Discogs
  • SongKong is designed to so it can be configured once and then all songs tagged the same way to easily ensure consistency over your music collection, then at a later date if you want to change how your music is tagged you can simply modify your preferences then apply the new rules to the whole collection
  • Most Music taggers concentrate on the basic metadata - artist, album, title, trackno, year and genre and not much alot else. But SongKong goes much deeper with many more specialist fields such as Performer, Opus, Instrument, Is Classical and Work. This continues with artwork, we can get artist artwork and back covers, not just album front covers
  • As part of the Melco integration we have worked closely with MinimServer to provide the additional metadata needed for serving Classical music correctly, this includes our unique algorithm that can distinguish between classical and non-classical albums
  • We also have done work so SongKong integrates with other software such as Roon, Naim, iTunes and Apple Music
  • Our Delete Duplicates task gives a unique level of control over not only identifying duplicates but deciding criteria to select which duplicates to delete and which to keep
  • Alternative taggers automated matching feature only working an album at a time, but only SongKong can be applied on a complete collection in one go
  • SongKong is designed to work over large amounts of data without failing, successfully being run on some music collections of over 1 million songs
  • Unlike most commercial software we have an open bug tracker so you can see what bugs are in the application and what improvements and new features we would like to add. We do this because we are completely open about the pros and cons of SongKong and want to work closely with our customers to make SongKong the best music tagger available, and welcome discussion on our forum