Comparison
data-juicer vs unstructured
Verdict
Pick data-juicer if a Python library for foundational AI model data processing, offering a pipeline for tasks like instruction tuning and synthetic data generation; 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.
Markdown twin · data-juicer alternatives · unstructured alternatives
GraphCanon updated Sep 20, 2026
14views this month
vs
Trust & integrity
| Signal | data-juicer | unstructured |
|---|---|---|
| Maintenance | Very active (4d since push) As of Aug 17, 2026 · github_public_v1 | Very active (3d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 17, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- data-juicer
- Data processing for and with foundation models
- unstructured
- Convert documents to structured data effortlessly
Stars
- data-juicer
- 6.9k
- unstructured
- 15k
Forks
- data-juicer
- 404
- unstructured
- 1.3k
Open issues
- data-juicer
- 59
- unstructured
- 309
Language
- data-juicer
- Python
- unstructured
- HTML
Adopt for
- data-juicer
- A Python library for foundational AI model data processing, offering a pipeline for tasks like instruction tuning and synthetic data generation.
- unstructured
- 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
- data-juicer
- -
- unstructured
- -
Runtime
- data-juicer
- -
- unstructured
- -
License
- data-juicer
- Apache-2.0
- unstructured
- Apache-2.0
Last pushed
- data-juicer
- Aug 13, 2026
- unstructured
- Sep 15, 2026
Categories
- data-juicer
- Data & Retrieval, Model Training
- unstructured
- Data & Retrieval, Developer Tools, Model Training
Trust and health
Days since push
- data-juicer
- 4d
- unstructured
- 3d
Open issues (now)
- data-juicer
- 59
- unstructured
- 309
Stars delta
- data-juicer
- +166 (30d)
- unstructured
- +208 (30d)
Open issues delta
- data-juicer
- -3 (30d)
- unstructured
- +32 (30d)
Full report
- data-juicer
- Trust report
- unstructured
- Trust report
Typed relationship
data-juicer depends on unstructuredData-Juicer processes data which could include the output from unstructured documents processed by unstructured.
Shared compatibility
- Python · data-juicer: Python runtime · unstructured: Python runtime
Choose data-juicer if…
- data-juicer is primarily Python; unstructured is HTML.
- Data-Juicer processes data which could include the output from unstructured documents processed by unstructured.
- Tags unique to data-juicer: foundation models, instruction-tuning, large-language-models, llm.
- When you need to preprocess large datasets specifically for training large language models (LLMs) with pipelines that support sophisticated processes like instruction tuning.
When NOT to use data-juicer
- If your project does not involve foundational AI model training or if you do not require advanced data processing capabilities such as synthetic data generation.
Choose unstructured if…
- unstructured is primarily HTML; data-juicer is Python.
- Data-Juicer processes data which could include the output from unstructured documents processed by unstructured.
- Tags unique to unstructured: data-pipelines, deep-learning, document-image-analysis, document-image-processing.
- Also covers Developer Tools.
- 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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (datajuicer/data-juicer) · observed Sep 20, 2026
- GitHub forks (datajuicer/data-juicer) · observed Sep 20, 2026
- Last push (datajuicer/data-juicer) · observed Aug 13, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Unstructured-IO/unstructured) · observed Sep 20, 2026
- GitHub forks (Unstructured-IO/unstructured) · observed Sep 20, 2026
- Last push (Unstructured-IO/unstructured) · observed Sep 15, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: data-juicer 6.9k · unstructured 15k (synced Sep 20, 2026).
Common questions
- What is the difference between data-juicer and unstructured?
- data-juicer: Data processing for and with foundation models. unstructured: Convert documents to structured data effortlessly. See the comparison table for live GitHub stats and shared categories.
- When should I choose data-juicer over unstructured?
- Choose data-juicer over unstructured when data-juicer is primarily Python; unstructured is HTML; Data-Juicer processes data which could include the output from unstructured documents processed by unstructured; Tags unique to data-juicer: foundation models, instruction-tuning, large-language-models, llm; When you need to preprocess large datasets specifically for training large language models (LLMs) with pipelines that support sophisticated processes like instruction tuning.
- When should I choose unstructured over data-juicer?
- Choose unstructured over data-juicer when unstructured is primarily HTML; data-juicer is Python; Data-Juicer processes data which could include the output from unstructured documents processed by unstructured; Tags unique to unstructured: data-pipelines, deep-learning, document-image-analysis, document-image-processing; Also covers Developer Tools; 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 data-juicer?
- If your project does not involve foundational AI model training or if you do not require advanced data processing capabilities such as synthetic data generation.
- 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 data-juicer or unstructured more popular on GitHub?
- unstructured has more GitHub stars (15,446 vs 6,897). Stars measure visibility, not whether either tool fits your constraints.
- Are data-juicer and unstructured open source?
- Yes - both are open-source projects on GitHub (data-juicer: Apache-2.0, unstructured: Apache-2.0).
- Where can I find alternatives to data-juicer or unstructured?
- GraphCanon lists graph-backed alternatives at data-juicer alternatives and unstructured alternatives (data-juicer markdown twin, unstructured markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, data-juicer or unstructured?
- data-juicer: 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 data-juicer and unstructured?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: data-juicer trust report; unstructured trust report.