About Seenit
Challenges
- From vast catalogs of videos, find short clips that meet specific requirements
- Evaluate, store, and search complex properties of video content
- Scale to accommodate a quickly growing business, including new features, large files, and massive amounts of data
Outcomes
- Full-Text Search allows sophisticated search on any combination of visual objects, words, and sentiments
- Video tags stored as JSON objects are searchable using wildcarding, fuzzy search, and Boolean search
- Couchbase scaled effortlessly, and a new search feature implementation was shortened from 12 weeks to 1 week
We already extensively use N1QL for our structured querying, but now with full-text search integrated into Couchbase, we can seamlessly search all this data and derive relevance-based intelligence using a single data platform.
Dave Starling CTO, Seenit
Industry
Use case
- Recommendation engine
- User profile
- Media catalog
