--- title: "hamilton vs unstructured" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/apache-hamilton-vs-unstructured-io-unstructured" tools: ["apache-hamilton", "unstructured-io-unstructured"] --- # hamilton vs unstructured *GraphCanon updated Sep 29, 2026* ## Verdict Pick hamilton if apache Hamilton aids Python data environments by enabling modular, self-documenting dataflows with lineage/tracing and metadata support; pick unstructured if unstructured is an open-source ETL solution for transforming complex documents into clean, structured formats for language models, supporting workflows like partitioning, enrichments, chunking, and embedding. [hamilton](https://hamilton.apache.org/) reports 2.6k GitHub stars, 215 forks, and 153 open issues, last pushed Sep 29, 2026. [unstructured](https://www.unstructured.io/) has 15k stars, 1.3k forks, and 309 open issues, last pushed Sep 15, 2026. Figures are from public GitHub metadata via [hamilton's repository](https://github.com/apache/hamilton) and [unstructured's repository](https://github.com/Unstructured-IO/unstructured). | | [hamilton](/tools/apache-hamilton.md) | [unstructured](/tools/unstructured-io-unstructured.md) | | --- | --- | --- | | Tagline | Modular dataflow definition for Python environments | Convert documents to structured data effortlessly | | Stars | 2,601 | 15,446 | | Forks | 215 | 1,330 | | Open issues | 153 | 309 | | Language | Jupyter Notebook | HTML | | Adopt for | Apache Hamilton aids Python data environments by enabling modular, self-documenting dataflows with lineage/tracing and metadata support. | Unstructured is an open-source ETL solution for transforming complex documents into clean, structured formats for language models, supporting workflows like partitioning, enrichments, chunking, and embedding. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Data & Retrieval, Developer Tools | Data & Retrieval, Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hamilton](/tools/apache-hamilton.md) | [unstructured](/tools/unstructured-io-unstructured.md) | | --- | --- | --- | | Days since push | 0d | 3d | | Open issues (now) | 153 | 309 | | Stars delta | +44 (30d) | +208 (30d) | | Open issues delta | +5 (30d) | +32 (30d) | | Full report | [trust report](/tools/apache-hamilton/trust.md) | [trust report](/tools/unstructured-io-unstructured/trust.md) | ## Shared compatibility - **Python**: [hamilton](/tools/apache-hamilton.md) - Python runtime; [unstructured](/tools/unstructured-io-unstructured.md) - Python runtime ## Decision facts: hamilton - **Adopt for:** Apache Hamilton aids Python data environments by enabling modular, self-documenting dataflows with lineage/tracing and metadata support. ## Decision facts: unstructured - **Adopt for:** Unstructured is an open-source ETL solution for transforming complex documents into clean, structured formats for language models, supporting workflows like partitioning, enrichments, chunking, and embedding. ## Choose when ### Choose hamilton if… - hamilton is primarily Jupyter Notebook; unstructured is HTML. - Tags unique to hamilton: dag, data-analysis, data-engineering, data-science. - Requires detailed lineage and tracing in Python-based ETL processes ### Choose unstructured if… - unstructured is primarily HTML; hamilton is Jupyter Notebook. - Tags unique to unstructured: data-pipelines, deep-learning, document-image-analysis, document-image-processing. - Also covers Model Training. - unstructured ships Docker support for self-hosted deployment. - When you need to convert a variety of document types, including PDFs and images, into structured data formats suitable for language models. ## When NOT to use hamilton - Working exclusively within a non-Python environment where broader platform support is needed - Projects that do not require extensive metadata capture or lineage tracking capabilities ## When NOT to use unstructured - If you are working with simple text files that do not require complex parsing or enrichment processes. - When you need a tool that supports real-time document processing, as Unstructured is optimized for batch processing and may not be suitable for real-time applications. - If you are looking for a solution that does not require setting up a Docker environment or managing dependencies with uv. - When you need a tool that supports a wider range of document types beyond PDFs and images, as Unstructured may not cover all your document format needs. ## Common questions ### What is the difference between hamilton and unstructured? hamilton: Modular dataflow definition for Python environments. unstructured: Convert documents to structured data effortlessly. See the comparison table for live GitHub stats and shared categories. ### When should I choose hamilton over unstructured? Choose hamilton over unstructured when hamilton is primarily Jupyter Notebook; unstructured is HTML; Tags unique to hamilton: dag, data-analysis, data-engineering, data-science; Requires detailed lineage and tracing in Python-based ETL processes. ### When should I choose unstructured over hamilton? Choose unstructured over hamilton when unstructured is primarily HTML; hamilton is Jupyter Notebook; Tags unique to unstructured: data-pipelines, deep-learning, document-image-analysis, document-image-processing; Also covers Model Training; unstructured ships Docker support for self-hosted deployment; When you need to convert a variety of document types, including PDFs and images, into structured data formats suitable for language models. ### When should I avoid hamilton? Working exclusively within a non-Python environment where broader platform support is needed Projects that do not require extensive metadata capture or lineage tracking capabilities ### When should I avoid unstructured? If you are working with simple text files that do not require complex parsing or enrichment processes. When you need a tool that supports real-time document processing, as Unstructured is optimized for batch processing and may not be suitable for real-time applications. If you are looking for a solution that does not require setting up a Docker environment or managing dependencies with uv. When you need a tool that supports a wider range of document types beyond PDFs and images, as Unstructured may not cover all your document format needs. ### Is hamilton or unstructured more popular on GitHub? unstructured has more GitHub stars (15,446 vs 2,601). Stars measure visibility, not whether either tool fits your constraints. ### Are hamilton and unstructured open source? Yes - both are open-source projects on GitHub (hamilton: Apache-2.0, unstructured: Apache-2.0). ### Where can I find alternatives to hamilton or unstructured? GraphCanon lists graph-backed alternatives at [hamilton alternatives](/tools/apache-hamilton/alternatives) and [unstructured alternatives](/tools/unstructured-io-unstructured/alternatives) ([hamilton markdown twin](/tools/apache-hamilton/alternatives.md), [unstructured markdown twin](/tools/unstructured-io-unstructured/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/apache-hamilton-vs-unstructured-io-unstructured.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hamilton or unstructured? hamilton: Very active. unstructured: Very active. 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 hamilton and unstructured? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hamilton trust report](/tools/apache-hamilton/trust); [unstructured trust report](/tools/unstructured-io-unstructured/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=apache-hamilton`](/api/graphcanon/graph?tool=apache-hamilton) - 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/_