Docling vs Tesseract
Both are alternatives to AWS Textract. Here's how they stack up — verified facts, no spin.
Also searched as Tesseract vs Docling — same comparison, one verdict.
Docling
TOP PICKIBM's document converter. Layout-aware PDF to clean Markdown, MIT.
Docling parses PDFs, Office documents, images and HTML into a structured representation that preserves reading order, tables, figures and headings, then exports to Markdown or JSON. It uses purpose-trained layout and table models rather than heuristics, which is why it holds up on multi-column academic papers and financial statements where simpler extractors interleave columns into nonsense. It integrates directly with LlamaIndex and Haystack, is MIT licensed, and runs entirely locally including on CPU.
Tesseract
Thirty years old, Apache-2.0, and it runs absolutely everywhere.
Tesseract is the OCR engine most of the world's text extraction has quietly gone through, originally from HP, developed by Google for a decade, and Apache-2.0 throughout. It recognises over a hundred languages, has bindings for every language you might be writing in, and is packaged in every Linux distribution. Modern neural extractors beat it on complex layouts, but on clean scanned text it is fast, dependable and effectively free of dependencies — often the right tool precisely because it is boring.
Side by side
| Docling | Tesseract | |
|---|---|---|
| Sovereignty Score | 94 | 95 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first | Yes | Yes |
| License | MIT | Apache-2.0 |
| Pricing | Free, MIT. Runs on your own hardware, CPU or GPU. | Free, Apache-2.0. |
Docling is Macrostack's recommended AWS Textract alternative, so it's our pick here.
Docling
Strengths
- +Layout-aware — preserves reading order, tables and structure
- +Outputs clean Markdown/JSON that drops into a RAG pipeline
- +Direct integrations with LlamaIndex and Haystack
- +MIT, fully local, no per-page cost
Trade-offs
- −Slower per page than cloud OCR on very large batches
- −Handwriting support is weak compared with Textract
- −No specialised invoice or receipt models
Tesseract
Strengths
- +Over a hundred languages, bindings for everything
- +Extremely mature and stable — decades of production use
- +Packaged everywhere; trivial to install and deploy
- +Apache-2.0 with no dependency weight
Trade-offs
- −Weak on complex layouts, multi-column pages and tables
- −Needs image pre-processing for good results on poor scans
- −No document understanding — it gives you text, not structure
Related alternative guides
Facts verified 2026-08-11. Licenses and pricing change — spotted something out of date? That's a correction we want.