V3 Memory Unification

To unify multiple memory systems, you must consolidate legacy modules like MemoryManager and SwarmMemory into a single AgentDB backend. This migration enables fast, cross-system memory retrieval using HNSW vector indexing.

HNSW indexing is a vector search mechanism used in backend architecture to enable fast, semantic retrieval across unified memory layers. It allows cross-system queries by indexing memory data within a single AgentDB storage backend.

Yes, you can migrate legacy components like SQLiteBackend and MarkdownBackend into AgentDB. The unification process integrates these disparate storage layers into a single scalable memory backend for unified querying.

Cross-agent memory sharing works by consolidating DistributedMemorySystem and SwarmMemory components into a unified AgentDB backend. This enables collaborative memory reuse across agents via integrated SONA learning and semantic vector search.

Implementing ADR-006 defines the Unified Memory Service required to enable cross-system memory queries. You also implement ADR-009 for the Hybrid Memory Backend to standardize AgentDB storage and HNSW indexing.

Unifying legacy memory layers into AgentDB requires migrating components like AdvancedMemoryManager and HybridBackend entirely. Limitations include the architectural overhead of transitioning disparate systems and ensuring compatibility with SONA learning integration.