AgentDB Advanced Features

You implement multi-database coordination by managing multiple AgentDB instances and applying domain-based sharding. This allows coordinated workflows across distributed databases, organizing data by specific domains for scalable architectures.

Yes, hybrid search combines vector similarity with metadata filtering. This feature allows you to perform vector search tasks while simultaneously applying strict metadata constraints, returning highly targeted results from your distributed system.

Yes, production deployment requires Node.js 18+ and AgentDB v1.0.7+ via agentic-flow. You also need a foundational understanding of distributed systems and vector search fundamentals to manage the architecture effectively.

Domain-based sharding is the recommended approach for distributed AI systems. By partitioning data across coordinated multi-databases based on specific domains, you achieve scalable architectures and optimized production-grade deployment patterns.

AgentDB allows you to master vector search by applying custom distance metrics. This capability lets you tailor similarity calculations within hybrid search tasks, combining vector similarities with metadata filtering for precise results.