DoclingvsSemantic Kernel

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

Docling

Data & ETL

IBM's document conversion tool for AI pipelines

Full review →Website ↗

Semantic Kernel

Developer Tools

Microsoft's AI orchestration SDK for building agents with .NET, Python, and Java

Full review →Website ↗
FeatureDoclingSemantic Kernel
CategoryData & ETLDeveloper Tools
PricingFree (open-source)Free (open-source)
GitHub Stars
15k
✓ More stars
23k
PlatformsLinux, macOS, WindowsLinux, macOS, Windows
Key Features
  • ✓ PDF conversion
  • ✓ Table extraction
  • ✓ OCR
  • ✓ Markdown output
  • ✓ LlamaIndex integration
  • ✓ Plugin system
  • ✓ Memory
  • ✓ Planner
  • ✓ Multi-language
  • ✓ Azure integration
Pros
  • + Excellent PDF parsing
  • + Table extraction
  • + OCR capability
  • + IBM Research quality
  • + LlamaIndex integration
  • + Enterprise-ready with Microsoft backing
  • + Multi-language (C#, Python, Java)
  • + Deep Azure OpenAI integration
  • + Plugin architecture for extensibility
Cons
  • − Heavy dependencies
  • − Can be slow on large docs
  • − Python only
  • − Complex output format
  • − Heavy enterprise focus
  • − Verbose API compared to alternatives
Tags
documentspdfconversionibm
microsoftsdkenterprisedotnet

Want to compare different tools?

← Back to compare picker

Related Comparisons

Docling vs LlamaIndex →Semantic Kernel vs LlamaIndex →Docling vs Crawl4AI →Semantic Kernel vs Crawl4AI →Docling vs Anthropic MCP →Semantic Kernel vs Anthropic MCP →Docling vs Gradio →Semantic Kernel vs Gradio →Docling vs Streamlit →Semantic Kernel vs Streamlit →Docling vs DSPy →Semantic Kernel vs DSPy →