Comparison
dify vs quilt
Verdict
Pick dify if dify is a platform for creating agentic workflows and RAG pipelines, supporting various AI models and tools, deployable on cloud, VPC, or self-hosted environments; pick quilt if quilt is a platform focused on managing scientific and AI-related datasets through detailed version control and context-rich data packages hosted on AWS.
Markdown twin · dify alternatives · quilt alternatives
GraphCanon updated Oct 4, 2026
8views this month
Trust & integrity
| Signal | dify | quilt |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 28, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 28, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Oct 4, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- dify
- Build Agentic workflows and RAG pipelines with rich AI model and tool support on one collaborative workspace.
- quilt
- Scientific Data Management Platform on AWS for managing data packages
Stars
- dify
- 156k
- quilt
- 1.4k
Forks
- dify
- 25k
- quilt
- 89
Open issues
- dify
- 1.1k
- quilt
- 119
Language
- dify
- TypeScript
- quilt
- TypeScript
Adopt for
- dify
- Dify is a platform for creating agentic workflows and RAG pipelines, supporting various AI models and tools, deployable on cloud, VPC, or self-hosted environments.
- quilt
- Quilt is a platform focused on managing scientific and AI-related datasets through detailed version control and context-rich data packages hosted on AWS.
Persona
- dify
- -
- quilt
- -
Runtime
- dify
- -
- quilt
- -
License
- dify
- Other
- quilt
- Apache-2.0
Last pushed
- dify
- Sep 18, 2026
- quilt
- Sep 27, 2026
Categories
- dify
- AI Agents, Data & Retrieval, Developer Tools
- quilt
- Data & Retrieval
Trust and health
Open issues (now)
- dify
- 1.1k
- quilt
- 119
Stars delta
- dify
- +4.5k (30d)
- quilt
- +3 (30d)
Open issues delta
- dify
- +172 (30d)
- quilt
- -24 (30d)
Full report
- dify
- Trust report
- quilt
- Trust report
Choose dify if…
- License: dify is Other, quilt is Apache-2.0.
- Tags unique to dify: agent, agentic-ai, agentic-framework, agentic-workflow.
- Also covers AI Agents, Developer Tools.
- When you need a collaborative workspace that supports rich AI model and tool integration for agentic workflows and RAG pipelines.
When NOT to use dify
- If your project does not require agentic workflows or RAG pipelines, and you are looking for a more general-purpose AI development tool.
- When you need a platform that does not require Docker and Docker Compose for setup, as Dify's quick start guide assumes these prerequisites.
- If your team prefers a platform with a different licensing model, as Dify uses a modified Apache 2.0 license with additional conditions.
Choose quilt if…
- License: quilt is Apache-2.0, dify is Other.
- Tags unique to quilt: data-engineering, data-version-control, data-versioning, parquet.
- When your team requires in-depth version control for complex scientific datasets, ensuring that every change to the dataset is tracked and documented.
When NOT to use quilt
- Not recommended if you prefer on-premises solutions over AWS-hosted services, as Quilt operates exclusively within the Amazon Web Services ecosystem.
- If your project involves handling simple and static datasets where traditional CVS tools suffice. The overhead of using a specialized solution like Quilt might not justify its use.
- Teams with limited experience in data engineering or with less sophisticated dataset requirements may find Quilt's robust features overly complex, potentially leading to underutilization.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (langgenius/dify) · observed Sep 20, 2026
- GitHub forks (langgenius/dify) · observed Sep 20, 2026
- Last push (langgenius/dify) · observed Sep 18, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Oct 4, 2026
- GitHub stars (quiltdata/quilt) · observed Sep 28, 2026
- GitHub forks (quiltdata/quilt) · observed Sep 28, 2026
- Last push (quiltdata/quilt) · observed Sep 27, 2026
- License file (Apache-2.0) · observed Sep 28, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: dify 156k · quilt 1.4k (synced Sep 20, 2026).
Common questions
- What is the difference between dify and quilt?
- dify: Build Agentic workflows and RAG pipelines with rich AI model and tool support on one collaborative workspace.. quilt: Scientific Data Management Platform on AWS for managing data packages. See the comparison table for live GitHub stats and shared categories.
- When should I choose dify over quilt?
- Choose dify over quilt when License: dify is Other, quilt is Apache-2.0; Tags unique to dify: agent, agentic-ai, agentic-framework, agentic-workflow; Also covers AI Agents, Developer Tools; When you need a collaborative workspace that supports rich AI model and tool integration for agentic workflows and RAG pipelines.
- When should I choose quilt over dify?
- Choose quilt over dify when License: quilt is Apache-2.0, dify is Other; Tags unique to quilt: data-engineering, data-version-control, data-versioning, parquet; When your team requires in-depth version control for complex scientific datasets, ensuring that every change to the dataset is tracked and documented.
- When should I avoid dify?
- If your project does not require agentic workflows or RAG pipelines, and you are looking for a more general-purpose AI development tool. When you need a platform that does not require Docker and Docker Compose for setup, as Dify's quick start guide assumes these prerequisites. If your team prefers a platform with a different licensing model, as Dify uses a modified Apache 2.0 license with additional conditions.
- When should I avoid quilt?
- Not recommended if you prefer on-premises solutions over AWS-hosted services, as Quilt operates exclusively within the Amazon Web Services ecosystem. If your project involves handling simple and static datasets where traditional CVS tools suffice. The overhead of using a specialized solution like Quilt might not justify its use. Teams with limited experience in data engineering or with less sophisticated dataset requirements may find Quilt's robust features overly complex, potentially leading to underutilization.
- Is dify or quilt more popular on GitHub?
- dify has more GitHub stars (156,243 vs 1,370). Stars measure visibility, not whether either tool fits your constraints.
- Are dify and quilt open source?
- Yes - both are open-source projects on GitHub (dify: Other, quilt: Apache-2.0).
- Where can I find alternatives to dify or quilt?
- GraphCanon lists graph-backed alternatives at dify alternatives and quilt alternatives (dify markdown twin, quilt 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, dify or quilt?
- dify: Very active. quilt: 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 dify and quilt?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dify trust report; quilt trust report.