head to head · open source
Dify vs J-Space-Cognition-Suite
Dify has 160,251 GitHub stars, 25,336 forks, 1,067 open issues and last shipped yesterday. J-Space-Cognition-Suite has 2,958 stars, 222 forks, 0 open issues and last shipped 2 months ago. Dify leads on adoption by 5,318% (160,251 vs 2,958 stars). Dify is written in Python under a custom or non-standard licence; J-Space-Cognition-Suite is written in Python under Apache-2.0. Dify has attracted 16% as many forks as stars, J-Space-Cognition-Suite 8%. Dify was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (ai, deepseek), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Dify | J-Space-Cognition-Suite | |
|---|---|---|
| GitHub stars | ★ 160K | ★ 3.0K |
| License | Custom / other | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-09-14 |
| Forks | ⑂ 25K | ⑂ 222 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Dify if
- You weight community size — 160K stars and counting
- You want the Custom / other license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick J-Space-Cognition-Suite if
- You want the J-Space-Cognition-Suite feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and J-Space-Cognition-Suite fits your workflow better
About Dify
Dify Cloud · Self hosting · Documentation · Dify edition overview Dify is an open source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. Here's a list of the core features: Quick start Before installing Dify, make sure your machine meets the following minimum system requirements: CPU = 2 Core RAM = 4 GiB The easiest way to start the Dify server is through Docker Compose. Before running Dify with the…
About J-Space-Cognition-Suite
J Space Cognition Suite SV1 Simplified Chinese J Space is an inference time workspace and control suite for complex reasoning, repository engineering, coordinated agents, and authorized security analysis. You install one skill, load relevant modules, and keep long task decisions connected to durable evidence. Its thirteen modules share one premise and one routing entry. Standard library Python scripts persist state, reread actual source text, detect stale maps and evidence, and return blocking results when a required condition is missing. The host supplies tools and agents. Quick start You need a host that can…
read the full J-Space-Cognition-Suite overview →
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Frequently asked questions
Is Dify or J-Space-Cognition-Suite more popular?
Dify has 160,251 GitHub stars and J-Space-Cognition-Suite has 2,958. Dify has the larger community by that measure.
Are Dify and J-Space-Cognition-Suite free?
Both are open source. Dify has no licence declared in this registry, and J-Space-Cognition-Suite is licensed under Apache-2.0. Both are free to self-host.
What is the difference between Dify and J-Space-Cognition-Suite?
Dify is written in Python and J-Space-Cognition-Suite in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Dify or J-Space-Cognition-Suite?
Choose Dify if you want the larger community (160,251 stars) or its Custom / other licence terms. Choose J-Space-Cognition-Suite if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.