Keywords AI

Docling vs R2R

Compare Docling and R2R side by side. Both are tools in the RAG Frameworks category.

Quick Comparison

	Docling	R2R
Category	RAG Frameworks	RAG Frameworks
Pricing	Open Source	open-source
Best For	Developers and researchers who need accurate document parsing with layout and table understanding	Developers wanting a production-ready RAG system
Website	github.com	sciphi.ai
Key Features	Document parsing with layout understanding Table extraction from PDFs OCR for scanned documents Multiple output formats Open-source and self-hosted	RAG engine End-to-end Deployable Open source
Use Cases	PDF to structured data conversion Academic paper processing Financial report extraction Scanned document digitization Document understanding pipelines	—

When to Choose Docling vs R2R

Choose Docling if you need

PDF to structured data conversion
Academic paper processing
Financial report extraction

Pricing: Open Source

About Docling

Docling is IBM's open-source document conversion toolkit that transforms PDFs, DOCX, PPTX, and other document formats into structured JSON or markdown. It uses advanced layout analysis and table structure recognition to preserve document structure, making it ideal for preparing documents for RAG and LLM applications. Docling integrates with LlamaIndex and LangChain for seamless pipeline construction.

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About R2R

End-to-end open-source RAG engine with server, API, and pipeline pre-built. RAG to Riches.

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What is RAG Frameworks?

Frameworks and tools for building retrieval-augmented generation pipelines—document parsing, chunking, indexing, and query engines that connect LLMs to your data.

Browse all RAG Frameworks tools →