Native Memory Core Graph Topology Export

The Problem

While standardizing the memory-core snapshot strategy, we realized that only the episodic memories and summaries vector collections were captured. The Native Edge Graph topology (storing runtime relationships, Nodes, and Edges) inside SQLite remained isolated and was omitted from the unified .neo-ai-data/backups/ export directory. Without serializing the graph alongside the vectors, downstream swarm clusters could suffer from "context amnesia" upon loading cold backups.

The Architectural Reality

The native Knowledge Graph leverages specific tables (Nodes, Edges) isolated inside SQLite.mjs, which differs structurally from traditional LanceDB/Chroma schemas. File modifications involve:

• ai/mcp/server/memory-core/services/DatabaseService.mjs: Augmented to explicitly query the GraphService.db.storage.db and synchronously pipe data to graph-backup-[timestamp].jsonl.
• Stream termination logic was fortified explicitly wrapping writeStream.end(resolve) in Promises to ensure that fast-exiting lifecycle scripts (exportDatabase.mjs) don't prematurely kill the pipe buffer before reaching the disk.

Avoided Anti-Patterns & False 'Gold Standards'

1. Purity of Context Collections: We intentionally avoided routing the graph through StorageRouter.mjs. While they share a database, the vector collections and the edge graph are structurally different. Building a generic router catch-all compromises the deterministic querying capabilities native directly to the Graph schema.
2. Synchronous Buffer Ejection: Previously, process.exit(0) truncated Node.js streams silently. Implementing deterministic await new Promise(...) checkpoints bypasses brittle event-emitter architectures while guaranteeing payload delivery regardless of execution environment speed.