Global Music Data
Built for Today’s Modern Music Business
Gracenote Global Music Data is built from the ground-up to support today’s playlist and track-based streaming models. With normalized data and standardized artist and recording IDs, Gracenote enables entertainment services to simplify how fans find and connect with the music they love.
A normalized dataset of Artists, Albums and Recordings lets entertainment services better manage music search across a sea of original releases, collaborations, remixes and live recordings.
Powering Advanced Discovery
Key editorial data and sonic descriptors like Genre, Mood, Era, Origin, Tempo and Artist Language enable music services to create finely tuned playlists to match the taste and vibe of fans.
Gracenote unique IDs connect Artists, Albums and Recordings across digital media, letting fans discover more of the music they love by linking them to artist appearances on late night TV, roles in movies and music videos.
Gracenote Global Music Data features deep descriptors for practically every song ever recorded. Leveraging Gracenote’s advanced machine learning technology and the industry’s finest editorial team, Gracenote data for Genre, Origin, Era, Artist Type, as well as Mood and Tempo is the secret sauce behind the hottest playlists.
Powering Voice and Text Search
In this era of connected IoT devices, finding your favorite jams no longer requires typing an artist name into a search bar. Gracenote Global Music Data provides structure, in the form of IDs and normalized data, to support the most innovative music search and discovery interfaces, from voice and gesture to virtual reality and beyond.
The Database of Record for Today’s Music Business
Normalized Recordings & Song Groups
Reduces track duplication by having a single representation for a unique recording and provides links between primary artists and their collaborations.
Recognizes artists with similar names and ensures the right recordings are associated with the right act.
Album Masters & Editions
Offers a clear representation of artist discographies through album masters and editions – optimized for digital services, as opposed to retail album sales.
Music data is normalized and organized for specific geographies and regions and features advanced descriptors localized in the Artist languages.