--- title: "opendataloader-pdf vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/opendataloader-project-opendataloader-pdf-vs-pathwaycom-llm-app" tools: ["opendataloader-project-opendataloader-pdf", "pathwaycom-llm-app"] --- # opendataloader-pdf vs llm-app *GraphCanon updated Sep 20, 2026* ## Verdict Pick opendataloader-pdf if opendataloader-pdf is an open-source PDF parsing library in Java that transforms PDFs into AI-ready data by supporting OCR recognition, bounding box generation, and table extraction; pick llm-app if llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. [opendataloader-pdf](https://opendataloader.org) reports 29k GitHub stars, 2.7k forks, and 82 open issues, last pushed Aug 18, 2026. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [opendataloader-pdf's repository](https://github.com/opendataloader-project/opendataloader-pdf) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [opendataloader-pdf](/tools/opendataloader-project-opendataloader-pdf.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | PDF Parser for AI-ready data | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data | | Stars | 28,528 | 58,920 | | Forks | 2,724 | 1,498 | | Open issues | 82 | 8 | | Language | Java | Jupyter Notebook | | Adopt for | Opendataloader-pdf is an open-source PDF parsing library in Java that transforms PDFs into AI-ready data by supporting OCR recognition, bounding box generation, and table extraction. | llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. | | Persona | - | - | | Runtime | - | - | | License | Opendataloader-pdf uses Apache License 2.0, making it a fully permissive license that allows easy integration into commercial projects without copyleft obligations. Prior to version 2.0, the tool was | MIT License | | Categories | Data & Retrieval, Model Training | Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [opendataloader-pdf](/tools/opendataloader-project-opendataloader-pdf.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 74d | | Open issues (now) | 82 | 8 | | Stars delta | +1.1k (30d) | -117 (30d) | | Open issues delta | +8 (30d) | 0 (30d) | | Full report | [trust report](/tools/opendataloader-project-opendataloader-pdf/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## Decision facts: opendataloader-pdf - **Adopt for:** Opendataloader-pdf is an open-source PDF parsing library in Java that transforms PDFs into AI-ready data by supporting OCR recognition, bounding box generation, and table extraction. - **License detail:** Opendataloader-pdf uses Apache License 2.0, making it a fully permissive license that allows easy integration into commercial projects without copyleft obligations. Prior to version 2.0, the tool was ## Decision facts: llm-app - **Pricing:** freemium - The repository is open-source under the MIT License, but additional services or support might incur costs. - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **Adopt for:** llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **License detail:** MIT License ## Choose when ### Choose opendataloader-pdf if… - opendataloader-pdf is primarily Java; llm-app is Jupyter Notebook. - License: opendataloader-pdf is Apache-2.0, llm-app is MIT. - Tags unique to opendataloader-pdf: a11y, accessibility, ai, bounding-box. - - **You require precise control:** Opendataloader-pdf offers detailed features such as bounding box generation and table extraction, which can be crucial when you need precise data positioning from un ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; opendataloader-pdf is Java. - License: llm-app is MIT, opendataloader-pdf is Apache-2.0. - Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.. - Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.. - Tags unique to llm-app: chatbot, hugging-face, llm, llm-local. - Also covers Evaluation & Observability, Inference & Serving. - When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti ## When NOT to use opendataloader-pdf - - **Non-Java Environment:** Since the tool is primarily developed in Java, it might not be suitable if your primary development environment or application is built around another language. ## When NOT to use llm-app - Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. - Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ## Common questions ### What is the difference between opendataloader-pdf and llm-app? opendataloader-pdf: PDF Parser for AI-ready data. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. See the comparison table for live GitHub stats and shared categories. ### When should I choose opendataloader-pdf over llm-app? Choose opendataloader-pdf over llm-app when opendataloader-pdf is primarily Java; llm-app is Jupyter Notebook; License: opendataloader-pdf is Apache-2.0, llm-app is MIT; Tags unique to opendataloader-pdf: a11y, accessibility, ai, bounding-box; - **You require precise control:** Opendataloader-pdf offers detailed features such as bounding box generation and table extraction, which can be crucial when you need precise data positioning from un. ### When should I choose llm-app over opendataloader-pdf? Choose llm-app over opendataloader-pdf when llm-app is primarily Jupyter Notebook; opendataloader-pdf is Java; License: llm-app is MIT, opendataloader-pdf is Apache-2.0; Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.; Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.; Tags unique to llm-app: chatbot, hugging-face, llm, llm-local; Also covers Evaluation & Observability, Inference & Serving; When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti. ### When should I avoid opendataloader-pdf? - **Non-Java Environment:** Since the tool is primarily developed in Java, it might not be suitable if your primary development environment or application is built around another language. ### When should I avoid llm-app? Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ### Is opendataloader-pdf or llm-app more popular on GitHub? llm-app has more GitHub stars (58,920 vs 28,528). Stars measure visibility, not whether either tool fits your constraints. ### Are opendataloader-pdf and llm-app open source? Yes - both are open-source projects on GitHub (opendataloader-pdf: Apache-2.0, llm-app: MIT). ### Where can I find alternatives to opendataloader-pdf or llm-app? GraphCanon lists graph-backed alternatives at [opendataloader-pdf alternatives](/tools/opendataloader-project-opendataloader-pdf/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([opendataloader-pdf markdown twin](/tools/opendataloader-project-opendataloader-pdf/alternatives.md), [llm-app markdown twin](/tools/pathwaycom-llm-app/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/opendataloader-project-opendataloader-pdf-vs-pathwaycom-llm-app.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, opendataloader-pdf or llm-app? opendataloader-pdf: Very active. llm-app: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for opendataloader-pdf and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [opendataloader-pdf trust report](/tools/opendataloader-project-opendataloader-pdf/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=opendataloader-project-opendataloader-pdf`](/api/graphcanon/graph?tool=opendataloader-project-opendataloader-pdf) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_