n8n-nodes-pgvector-advanced
Advanced PGVector nodes for n8n with full CRUD control. No more limitations of the built-in node.
Install in 30 Seconds
bash <(curl -fsSL https://raw.githubusercontent.com/aaron777collins/BetterPGVectorN8N/main/install.sh)
The installer auto-detects your setup and does the right thing.
Full Installation Guide Quick Start
Why Use This?
| Built-in PGVector Node | This Package |
|---|---|
| Insert only | Full CRUD (Upsert, Query, Delete, Get) |
| No stable IDs | External IDs for reliable syncing |
| Basic queries | Filters, pagination, multiple distance metrics |
| Single inserts | Batch operations (1000+ embeddings) |
| Manual schema | Auto table/index creation |
Features
- Full CRUD Operations - Upsert, Query, Delete, and Get embeddings with complete control
- Stable IDs - Support both internal UUIDs and external IDs for reliable upstream integration
- Advanced Querying - Vector similarity search with metadata filters, pagination, and multiple distance metrics
- Batch Operations - Efficient batch inserts and updates (1000+ embeddings)
- Schema Management - Automatic table creation, indexing (HNSW/IVFFlat), and schema validation
- Production-Ready - Connection pooling, error handling, retries, and comprehensive testing
- Type-Safe - Full TypeScript implementation with strict typing
Quick Links
| Guide | Description |
|---|---|
| Installation | All installation methods (Docker, npm, UI) |
| Quick Start | Get up and running in 5 minutes |
| Operations | Complete reference for all operations |
| Docker Guide | Persistent Docker installation |
| API Reference | TypeScript API and database schema |
| Troubleshooting | Common issues and solutions |
Example Workflow
1. Parse documents
2. Generate embeddings (OpenAI, Cohere, etc.)
3. Upsert to PGVector with metadata
4. Query similar documents
5. Use results in your workflow
License
MIT
Made with ❤️ for the n8n community