Add IBM Db2 Vector Store node for AI workflows in n8n

Feature Requests Nodes
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It would help if there was a node for:

IBM Db2 Vector Store in n8n, following the existing vector store node pattern used by providers like PGVector and Pinecone.

Our use case:

We want to use IBM Db2 as the backend for AI workflows in n8n, particularly for:

  • Document embedding storage

  • Semantic search / vector retrieval

  • Retrieval-Augmented Generation (RAG) workflows

  • Enterprise use cases where structured business data and vector data should reside within the same database platform

  • Agent workflows where the vector store can be used as a retriever or tool

Db2 is especially relevant for enterprise teams already using it for operational workloads and governance. A native n8n node would simplify building AI workflows without requiring data movement to a separate vector-only platform.

The most useful initial step would be a Db2 Vector Store node with behavior similar to existing n8n vector store nodes, including:

  • Inserting documents with embeddings

  • Loading and retrieving documents

  • Metadata-aware retrieval (if supported)

  • Compatibility with retriever-based flows

  • Compatibility with tool / agent workflows

Potential future extensions could include:

  • Db2 Chat Memory support

  • A Db2 SQL node (as a separate node) if it aligns with n8n’s scope

Any resources to support this?

Recent ecosystem update (important):

IBM has recently introduced an official Db2 integration for LangChain:

This is an open-source Python connector that enables Db2 to function as a vector store within LangChain workflows, supporting use cases like RAG and AI agents. (IBM)

It allows developers to:

  • Store and manage vector embeddings directly in Db2

  • Perform semantic search and similarity queries

  • Build AI pipelines using Db2 as a native vector backend

Additionally, LangChain now provides a dedicated langchain-db2 integration package with support for vector storage, similarity search, and metadata filtering. (LangChain Docs)

This further reinforces that Db2 already aligns with the same architectural pattern used by existing n8n vector store providers.

Relevant n8n implementation references:

IBM Db2 references:

Are you willing to work on this?

Yes — we are willing to explore and contribute this, starting with a scoped initial implementation aligned with n8n’s existing vector store architecture.