Vector Store
A vector store holds embeddings and finds the ones closest to a query. It is the retrieval half of RAG, and Db2 for i has no vector store as of 2026.
A vector store holds embeddings, the numeric representations a model produces for a passage of text, an image or another piece of content, and answers nearest-neighbor queries over them so a system can find the handful of passages most relevant to a question. That retrieval step is the first half of retrieval-augmented generation. The language model only does the second half.
For an IBM i shop this term matters because of an absence. IBM's Db2 for Linux, UNIX and Windows added a native VECTOR data type in Db2 12.1.2 in June 2025, so embeddings can sit in a table beside business data and be searched with SQL distance functions. Db2 for i did not get the equivalent, and the July 2026 Technology Refreshes for IBM i 7.6 and 7.5 added no AI items at all. As of September 2026 there is no vector store in Db2 for i and IBM has not published a date for one.
That puts the index outside the database. IBM's stated direction is OpenSearch running on Power, with Db2 for i remaining the system of record and OpenSearch holding the embedded, searchable copy an AI agent queries. Two practical consequences follow. The vector store is a second system to run, secure and back up. And it holds a readable copy of everything you indexed into it, inheriting none of your Db2 for i object authority automatically.
Related Terms
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation hands a language model passages pulled from your own data, so it answers from your content. On IBM i, retrieval is the hard half.
OpenSearch
OpenSearch is the open-source hybrid search engine IBM has positioned as the vector, text and structured search layer for RAG on Power, since Db2 for i has none.
Db2 for i
The relational database management system built into every IBM i operating system, tightly integrated with IBM i rather than a separately installed database product.
IBM i MCP Server
An open-source, IBM-published server implementing the Model Context Protocol (MCP), letting AI agents and LLMs query Db2 for i data and take defined actions on IBM i using natural language. In beta since October 2025.
Large Language Model (LLM)
A machine learning model trained on large volumes of text, used as the underlying technology behind generative AI tools including IBM Bob and general-purpose assistants like ChatGPT and Claude.
Foundation Model
A large, general-purpose AI model trained on broad data and then adapted, through prompting, tuning, or fine-tuning, to specific tasks such as RPG code generation.