Qdrant
Qdrant is a high-performance vector database for similarity and semantic search based on embeddings. It provides low latency, scalable replication, persistence, metadata filtering, a REST and gRPC API and client libraries. Common use cases include semantic search, recommendation systems, semantic classification and retrieval-augmented generation; it can be run on-premises or hosted.
This block bundles baseline information, context, and relations as a neutral reference in the model.
Reference building block
This building block serves as a structured reference in the knowledge model, with core data, context, and direct relationships.
What is this view?
This page provides a neutral starting point with core facts, structure context, and immediate relations—independent of learning or decision paths.
Baseline data
Context in the model
Structural placement
Where this block lives in the structure.
No structure path available.
Relations
Connected blocks
Directly linked content elements.