qmd vs azure-search-openai-demo
Two of the top projects in RAG and search, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
qmd
Local hybrid search over markdown notes and docs, with CLI and MCP server
azure-search-openai-demo
Azure RAG chat reference on AI Search and Azure OpenAI
Verdict
qmd ranks higher, 80 to 74. Of the 4 score parts we measure for both, qmd leads on 2, azure-search-openai-demo on 1 and 1 is even.
- Adoptionqmd leads by 18 points, 89 to 71: a wide gap.
- FreshnessEven at 100.
- Maintenanceazure-search-openai-demo leads by 1 point, 64 to 63: close to even.
- Agent-readyqmd leads by 10 points, 40 to 30.
Pick qmd if you are
Developers who want local search over notes and docs for agents
- Hybrid pipeline: query expansion, BM25 plus vector search, RRF fusion, then LLM reranking
- Runs on-device with GGUF models via node-llama-cpp; no hosted API needed
Pick azure-search-openai-demo if you are
Teams on Azure wanting the vendor-maintained RAG starting point
- Optional Entra login with per-document access control and Cosmos DB chat history
- Evaluation, safety evaluation, monitoring and productionizing guides in docs/
| What we compare | qmd | azure-search-openai-demo |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 89, widely used | 71, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 63, fair | 64, fair |
| Agent-ready | 40, minimal | 30, minimal |
| Facts from GitHub and the README | ||
| Stars | 30.8k | 7.8k |
| License | MIT (permissive) | MIT (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Aug 2026 | Oct 2026 |
| Language | TypeScript | Python |
| Docker | No | No |
| GPU | Optional | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
qmd
QMD indexes markdown notes, transcripts and docs into a SQLite store and searches them with BM25 (FTS5), vector search and LLM reranking. Models run locally as GGUF through node-llama-cpp. It ships a CLI with JSON and file-list output for agents, an MCP server over stdio or HTTP (default port 8181), and a Node/Bun SDK.
Who it is for: Developers who want local search over notes and docs for agents
Strengths
- Hybrid pipeline: query expansion, BM25 plus vector search, RRF fusion, then LLM reranking
- Runs on-device with GGUF models via node-llama-cpp; no hosted API needed
- CLI, MCP server (stdio or HTTP) and TypeScript SDK available
- HTTP server rejects non-loopback Origin and Host headers to block DNS rebinding
Weaknesses
- HTTP endpoints are unauthenticated; off-host use needs your own auth in front
- Built around markdown and text; other document formats are not mentioned
- Embedding step must run before semantic search works
- TypeScript, GGUF, qwen3-reranker
- Needs Node.js or Bun, node-llama-cpp, SQLite
azure-search-openai-demo
The canonical Azure RAG sample: a Python (Quart) backend and React frontend answering multi-turn questions over your documents with citations and a visible thought process, using Azure AI Search for retrieval and Azure OpenAI for generation. azd up provisions Container Apps, AI Search, Document Intelligence and Blob storage, with optional Cosmos DB chat history, Entra login with document ACLs, multimodal and speech. For teams already on Azure.
Who it is for: Teams on Azure wanting the vendor-maintained RAG starting point
Strengths
- Optional Entra login with per-document access control and Cosmos DB chat history
- Evaluation, safety evaluation, monitoring and productionizing guides in docs/
- Multimodal, speech and agentic retrieval are switchable features
- Commits within the last week; tests included
Weaknesses
- Cannot run locally until azd up has provisioned Azure resources
- Provisions paid services by default (AI Search, Document Intelligence); run azd down
- Azure OpenAI only; no other provider path
- README itself says not production-ready without extra security work
- Python, azure-openai
- Needs azure-subscription, azd, azure-ai-search, azure-openai, azure-document-intelligence, azure-blob-storage
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