VEKTOR Memory
Node.js/TypeScript-native memory layer. SQLite + local Transformers.js embeddings (~80MB model via WebAssembly). AUDN loop (Add/Update/Delete/None) resolves contradictions before write rather than at retrieval — read-after-write consistency.
At a glance
- Type
- Local-SQLite + AUDN-loop + TypeScript-native
- Tier
- T2
- Section
- Dedicated memory layers
- Created
- searched not found
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- $9/month subscription OR one-time $159 commercial license (activates on up to 3 machines)
- Funding
- searched not found
Taxonomy
- storage
- relational
- retrieval
- similarity
- persistence
- cross-session
- update
- extraction
- unit
- fact
- governance
- inspectable
- conflict
- llm-arbitrate
When to use
Optimised for: TypeScript-native developer experience
Anti-fit: not for Python-only stacks
Pros & cons
Pros
Vector-native memory framework with built-in embedding pipeline; minimal setup for new agents.
Cons
Vector-only — no graph or KV layer; smaller ecosystem.
Claims & capabilities
Only production-grade memory library targeting Node.js agents specifically with no cloud dependency. Python port on roadmap.
Technical surface
- API surface
- searched not found
- Backend storage
- searched not found
- Deployment
- Local-only (Node.js; Transformers.js via WebAssembly; SQLite; no cloud infrastructure)
- Embedding model
- searched not found
- Multi-tenancy
- searched not found
- MCP
- not documented publicly
- A2A
- not documented publicly
- OpenTelemetry
- not documented publicly
Similar systems
Other dedicated memory layers in the catalog, ranked by inbound references.
- Mem0 T1
Universal memory layer for AI agents. Three concurrent stores (vector + graph + KV); LLM-extracted facts; concurrent retrieval via ThreadPoolExecutor.
- Zep & Graphiti T1
Bi-temporal knowledge graph (event time + ingestion time). Strong on chronological reasoning and contradiction tracking. Graphiti is the open-source core.
- Cognee T1
"Extract–Cognify–Load" pipeline that turns raw input into a typed, queryable knowledge graph for agent recall.
- Hindsight (Vectorize) T1
Standalone memory service from Vectorize. Open source. Biomimetic four-network design (World, Bank, Observation, Opinion). Ships an MCP memory server.
- Memvid T2
Single-file memory layer (one .mv2 file). No DB, no server. Append-only sequence of immutable Smart Frames with timestamps + checksums. Native Rust core (rewritten from Python).
- Supermemory T1
Memory engine with API, app, browser extension, and MCP server. Extracts facts, tracks updates, resolves contradictions, auto-forgets expired info. Plugins for Claude Code, OpenCode, OpenClaw, Hermes.