Discussion
Vectors, meet Virtuoso.
Native HNSW vector indexing has landed in the Virtuoso Open Source develop/7 branch, with ONNX-based text embeddings, optimizer tuning, Windows build support and the new VVec console alongside.
Similarity search across native relational tables via SQL and RDF graphs via SPARQL, one engine.
Branch-level today, ahead of a release. Enjoy!
Architectural visualization.
#VectorSearch #VirtuosoRDBMS #SQL #SPARQL #AI #LLMs #KnowledgeGraph #Database
ONNX provides the bridge btw Virtuoso and local embedding models. By default, local embeddings are IBM’s granite-embedding-30m-english model based. Users can also use alternative models.
Embeddings from OpenAI, OpenAI-compatible APIs, etc. r also options for vector generation.
Showcasing the impact of vector similarity search on a DBpedia instance where embeddings have been generated and indexed on literal objects in a DBpedia knowledge graph.
#VectorSimilarity #DBpedia #SPARQL #VirtuosoRDBMS #HowTo #AI
Install Fedizen
Get the full app experience
The commits, straight from the source:
HNSW indexing: https://github.com/openlink/virtuoso-opensource/commit/3d6a0d5
Merge into develop/7: https://github.com/openlink/virtuoso-opensource/commit/d166c69
Full history: https://github.com/openlink/virtuoso-opensource/commits/develop/7/
Commits · openlink/virtuoso-opensource
Merge branch 'feature/vvec' into develop/7 · openlink/virtuoso-opensource@d166c69
Added native HNSW vector index support to the database engine · openlink/virtuoso-opensource@3d6a0d5