Readme
Source
- Canonical Cookbook page: https://developers.openai.com/cookbook/examples/vector_databases/singlestoredb/readme
- OpenAI Cookbook source: https://github.com/openai/openai-cookbook/blob/main/examples/vector_databases/SingleStoreDB/README.md
- Raw source: https://raw.githubusercontent.com/openai/openai-cookbook/main/examples/vector_databases/SingleStoreDB/README.md
- Source path:
examples/vector_databases/SingleStoreDB/README.md - Source kind:
examples - Source format:
.md - License basis: OpenAI Cookbook repository MIT license.
- Content hash:
bdba1125e8947ac465b18a81de92d17a01325581d4c17db1612e0ffbef66d629
Classification
- Primary category: RAG / retrieval / vector databases
- Wiki collection: 2026-05-15-openai-cookbook
- Taxonomy page: openai-cookbook-taxonomy
- Topic hub: openai-cookbook
Summary
SingleStoreDB has first-class support for vector search through our Vector Functions. Our vector database subsystem, first made available in 2017 and subsequently enhanced, allows extremely fast nearest-neighbor search to find objects that are semantically similar, easily using SQL. SingleStoreDB supports vectors and vector similarity search using dot produc…
What This Teaches
- How to connect OpenAI models with retrieval, embeddings, or external knowledge stores.
Implementation Use Cases
- Use as a concrete implementation reference when building OpenAI API systems in this category.
- Compare against current official API docs before copying model names, SDK calls, or parameters into production code.
- Preserve this page as a mirrored source; prefer synthesis pages for personal recommendations or project-specific decisions.
Mirrored Content
SingleStoreDB has first-class support for vector search through our Vector Functions. Our vector database subsystem, first made available in 2017 and subsequently enhanced, allows extremely fast nearest-neighbor search to find objects that are semantically similar, easily using SQL.
SingleStoreDB supports vectors and vector similarity search using dot_product (for cosine similarity) and euclidean_distance functions. These functions are used by our customers for applications including face recognition, visual product photo search and text-based semantic search. With the explosion of generative AI technology, these capabilities form a firm foundation for text-based AI chatbots.
But remember, SingleStoreDB is a high-performance, scalable, modern SQL DBMS that supports multiple data models including structured data, semi-structured data based on JSON, time-series, full text, spatial, key-value and of course vector data. Start powering your next intelligent application with SingleStoreDB today!
Example
This folder contains examples of using SingleStoreDB and OpenAI together. We will keep adding more scenarios so stay tuned!
| Name | Description |
|---|---|
| OpenAI wikipedia semantic search | Improve ChatGPT accuracy through SingleStoreDB semantic Search in QA |