AgentDB Advanced Features

Distributed AI database synchronization uses QUIC-based replication to achieve sub-millisecond data consistency across multiple AgentDB instances. You configure sync ports and peer host addresses directly within the database adapter initialization parameters.

Hybrid vector search combines vector similarity queries with metadata filtering to refine results in AI reasoning tasks. It operates across multi-database deployments using custom distance metrics to evaluate and route relevant data.

Multi-database coordination allows separate databases per domain or task with cross-database routing. This enables distributed AI workloads to manage distinct datasets while maintaining synchronized state across configured peer nodes.

Configuring QUIC peers requires enabling QUIC sync during adapter initialization and specifying a sync port alongside an array of peer host addresses. This establishes sub-millisecond data replication channels for production environments.

Custom distance metrics are used in distributed vector search when standard similarity calculations fail to capture domain-specific relationships. They enable scalable AI reasoning by tailoring hybrid search relevance to specific multi-database requirements.