V3 Memory Unification

Consolidating disparate memory systems into a unified AgentDB backend provides a single source of truth for cross-agent memory sharing. A UnifiedMemoryService coordinates this by orchestrating an AgentDBAdapter, an HNSWIndexer, and a DataMigrator.

HNSW vector search accelerates retrieval by indexing embeddings within the unified AgentDB, achieving 150x to 12,500x search performance improvements. The HNSWIndexer builds and queries this graph structure for fast similarity searches.

Yes, you can migrate data from SQLite and Markdown backends into a unified AgentDB. The DataMigrator component handles transferring existing records, while the AgentDBAdapter maps them into the new schema with embedding support.

The best way to unify MemoryManager and DistributedMemorySystem storage is migrating their data into a single AgentDB. This replaces fragmented backends with a unified interface leveraging HNSW indexing for accelerated retrieval.

AgentDB supports cross-agent memory sharing through a unified interface that maintains backward compatibility with legacy systems like SwarmMemory and AdvancedMemoryManager. This allows agents to access shared memory without breaking existing integrations.

You should migrate legacy memory systems to a vector database backend when retrieval latency bottlenecks agent performance or cross-agent data sharing is required. Unifying systems like HybridBackend into AgentDB with HNSW indexing resolves these scaling limitations.