opendataloader-pdf
OpenDataLoader PDF is an Apache 2.0 open-source Java library that extracts structured data (Markdown, JSON, HTML) from PDFs with bounding boxes for every element. It also auto-tags untagged PDFs into Tagged PDFs for accessibility compliance, with deterministic local processing and optional AI-hybrid mode for complex documents.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | opendataloader-project/opendataloader-pdf |
| Owner | opendataloader-project |
| Primary language | Java |
| License | Apache-2.0 — OSI-approved |
| Stars | 26.4k |
| Forks | 2.5k |
| Open issues | 69 |
| Latest release | v2.4.7 (2026-05-27) |
| Last updated | 2026-07-06 |
| Source | https://github.com/opendataloader-project/opendataloader-pdf |
What opendataloader-pdf is
Java 11+ PDF parser offering two processing modes: deterministic local extraction (0.015s/page) with XY-Cut++ reading order, or hybrid mode routing complex pages to AI backend (0.463s/page, 0.907 benchmark accuracy). Includes OCR support (80+ languages), table detection, formula extraction, and auto-tagging to Tagged PDF structure following Well-Tagged PDF specification.
Get the opendataloader-pdf source
Clone the repository and explore it locally.
git clone https://github.com/opendataloader-project/opendataloader-pdf.gitcd opendataloader-pdf# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Java 11+ runtime is mandatory; Python/Node.js SDKs are wrappers. Batch operations via Python spawn new JVM per call—consider pooling or direct Java usage for high-volume workflows.
- Local mode is deterministic and fast (0.015s/page) but lower accuracy (~0.831); hybrid mode requires external AI backend (details not provided) and is ~30x slower (0.463s/page). Choose mode based on accuracy vs. latency requirements.
- Outputs include bounding boxes for all elements, enabling precise source attribution in RAG, but downstream chunking logic must account for multi-coordinate elements (tables, images).
- Auto-tagging generates Tagged PDF; converting to PDF/UA-1/2 compliance is a separate enterprise step. Verify enterprise feature cost and SLA before committing to accessibility workflows.
- OCR support (80+ languages) and formula extraction are hybrid-mode only. Validate performance on your document types (scans, formulas) in hybrid mode before production deployment.
When to avoid it — and what to weigh
- Non-PDF document formats required — Project explicitly supports PDFs only. Does not process Word, Excel, PowerPoint, or other document types.
- GPU acceleration required — No GPU support mentioned. Local mode runs on CPU; hybrid mode routes to unspecified backend. Not suitable for real-time streaming or latency-critical single-document processing at scale.
- Proprietary/closed-source mandate — Core is Apache 2.0 (commercial-friendly), but PDF/UA export and accessibility studio are enterprise add-ons. Licensing model for enterprise features not clearly specified.
- Minimal dependencies or embedded constraints — Requires Java 11+ runtime. Each Python convert() call spawns a new JVM process, creating overhead for batch operations. May be unsuitable for lightweight embedded or serverless contexts.
License & commercial use
Apache License 2.0 (permissive OSI license). Allows commercial use, modification, and distribution with attribution and liability disclaimer. Core data extraction and auto-tagging are Apache 2.0. PDF/UA export and accessibility studio are enterprise add-ons with unknown licensing terms.
Apache 2.0 permits commercial use of core features (data extraction, auto-tagging to Tagged PDF) without license fees or proprietary restrictions. Enterprise features (PDF/UA export, accessibility studio) require separate commercial agreement. Verify enterprise licensing terms and support model with vendor before committing to production accessibility workflows.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Strong |
| Assessment confidence | High |
Project includes AI safety filters (prompt injection filtering) and header/footer/watermark filtering. No known vulnerabilities or security advisories mentioned. Java 11+ is long-term supported. Hybrid mode routes data to unspecified external backend—verify data residency, encryption, and compliance (GDPR, HIPAA) before using with sensitive PDFs. Local deterministic mode does not require external network calls.
Alternatives to consider
docling (MIT)
0.882 benchmark score (vs. 0.907), similar open-source positioning, faster table extraction (0.887). MIT license more permissive than Apache 2.0 for some use cases. Trade-off: slightly lower overall accuracy.
Nutrient (Commercial)
0.885 benchmark, fastest speed (0.008s/page), mature commercial product. Best if speed is critical and budget allows. Trade-off: proprietary license, no auto-tagging or accessibility focus.
Unstructured (Apache 2.0)
Broader document support (email, HTML, images). Same permissive license. Lower benchmark scores (0.686–0.841) and slower speeds (0.077–3.008s/page) for PDFs. Better for multi-format pipelines; weaker PDF specialist.
Build on opendataloader-pdf with DEV.co software developers
OpenDataLoader PDF is Apache 2.0 open-source with proven benchmark accuracy (#1 at 0.907). Local deterministic mode or AI hybrid. Auto-tag to Tagged PDF for regulatory compliance. Explore integration or enterprise PDF/UA features.
Talk to DEV.coRelated on DEV.co
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opendataloader-pdf FAQ
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Software development & web development with DEV.co
Need help beyond evaluating opendataloader-pdf? DEV.co is a software development agency offering software development services and web development for teams of every size. Our software developers and web developers build custom software, web applications, APIs, and rag frameworks integrations — and maintain them long-term.
Need PDF extraction or accessibility automation at scale?
OpenDataLoader PDF is Apache 2.0 open-source with proven benchmark accuracy (#1 at 0.907). Local deterministic mode or AI hybrid. Auto-tag to Tagged PDF for regulatory compliance. Explore integration or enterprise PDF/UA features.