LlamaIndex vs OpenRAG
LlamaIndex
llamaindex.aiOpenRAG
open-rag.aiSide by side
| Figure | LlamaIndex | OpenRAG |
|---|---|---|
| Price from | $50/mo | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 2 |
| Spec score · LLM Application Development Frameworks | 7.7 (#9) | 8.3 (#5) |
| Spec score · Retrieval-Augmented Generation Tools | 7.7 (#16) | 8.4 (#8) |
| Integrations | LlamaIndex documents community integrations for data loaders, agent tools, LLMs, vector stores, observability, and application frameworks. | The product documents compatibility with OpenAI API clients and names Open WebUI, LangChain, n8n and Twake.ai as integrations. |
| Purpose | LlamaIndex helps developers and enterprises automate document processing and build AI workflows around documents. | OpenRAG is a modular framework for building document-grounded retrieval-augmented generation systems. |
| Security | The pricing FAQ says LlamaParse is certified for SOC 2 Type II, GDPR, and HIPAA. | The site describes fail-closed scopes, verified outbound connections, redacted secrets, non-root containers, rate limiting and security headers. |
| Support | The listed support levels are community for Free, basic email support for Starter, priority Slack Connect for Pro, and dedicated support for Enterprise. | The product site directs technical questions to GitHub issues and links to documentation and a contact form. |
Plans
LlamaIndex
- Starter$50 a month
- Pro$500 a month
- EnterprisePriced on request
- FreePrice not published
OpenRAG
- OpenRAG (AGPL-3.0 self-hosted)Free
- Managed OpenRAG servicePriced on request
In their own words
LlamaIndex
LlamaIndex is a freemium platform for developers and enterprises automating document processing and AI workflows. LlamaParse handles more than 50 unstructured file types, including files with embedded images, complex layouts, multi-page tables and handwritten notes. Schema-based, language-model extraction agents convert unstructured content into structured insights without training. Workflows can divide documents into logical sections and classify them using natural-language descriptions and rules. Chunking and embedding pipelines support indexing and retrieval in RAG workflows. Community integrations cover data loaders, agent tools, language models, vector stores, observability and application frameworks. LlamaCloud connectors currently include Google Drive, SharePoint, S3 and Confluence. Free and Starter plans allow five concurrent parse, extract, classify and split jobs; Pro allows 20 and Enterprise 100. The Free plan has no listed price; Starter costs $50.00 per month. LlamaParse is commercial, while LlamaIndex and Workflows are open-source.
OpenRAG
OpenRAG is a modular framework for building systems that answer questions using documents as their grounding. Its retrieval combines semantic search with BM25 keyword matching and multilingual reranking; answers cite a source document and page, with links to the cited location. Document processing covers listed text, office, email, audio, video, and image formats, with PDF layout awareness, OCR, image captioning, and audio transcription. The product includes an admin console, chat interface, and OpenAI-compatible API, and can connect to user-provided models or a hosted provider. Partition isolation, owner, editor, and viewer roles, plus token or OpenID Connect authentication, are among its access controls. It can run on infrastructure controlled by the deployer, keeping documents, embeddings, and queries within that environment. The self-hosted AGPL-3.0 edition is listed at free. Deployment prerequisites are Docker, Docker Compose, and at least 16 GB of RAM; a CPU-only profile is optional. CSV, ODT, and HTML support, tool calling, agentic RAG, MCP, and encryption in transit and at rest are listed as coming soon.