AgentDB Advanced Features

Distributed vector synchronization is achieved using QUIC-based encrypted UDP replication to broadcast events across nodes, ensuring sub-millisecond cross-node updates for multi-node AI systems.

Hybrid vector search combines vector similarity metrics like cosine or euclidean with metadata filters and weighted scoring, applying MMR diversity to balance relevance and novelty in search results.

Multi-database sharding is supported alongside connection pooling, retry/backoff strategies, and monitoring, enabling scalable vector management across distributed AI infrastructure.

Vector similarity search supports configurable distance metrics including cosine, euclidean, dot product, and custom metrics, allowing flexible weighted scoring within hybrid vector and metadata queries.

QUIC encrypted UDP sync is needed for real-time multi-agent coordination requiring synchronized memories across geographically distributed nodes to serve low-latency recommendations and reasoning.

Distributed vector stores require careful configuration of sharding, connection pooling, and retry/backoff to maintain performance, and may face constraints when handling complex hybrid vector and metadata queries at scale.