head to head · open source
OpenClaw vs DeepAnalyze
OpenClaw has 393,747 GitHub stars, 82,755 forks, 6,671 open issues and last shipped yesterday. DeepAnalyze has 4,769 stars, 751 forks, 27 open issues and last shipped yesterday. OpenClaw leads on adoption by 8,156% (393,747 vs 4,769 stars). OpenClaw is written in TypeScript under MIT; DeepAnalyze is written in Python under MIT. OpenClaw has attracted 21% as many forks as stars, DeepAnalyze 16%. OpenClaw was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai), 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.
← all 20902 open source comparisons
Side by side
| OpenClaw | DeepAnalyze | |
|---|---|---|
| GitHub stars | ★ 394K | ★ 4.8K |
| License | MIT | MIT |
| Written in | TypeScript | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 83K | ⑂ 751 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick OpenClaw if
- You weight community size — 394K stars and counting
- You want the MIT license terms
- Your stack matches TypeScript
- You value the larger contributor base for long-term maintenance
pick DeepAnalyze if
- You want the DeepAnalyze feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and DeepAnalyze fits your workflow better
About OpenClaw
OpenClaw 🦞 — Your assistant, on your devices, in your chats OpenClaw is an open source AI assistant that runs on your own computer and meets you in the channels you already use: Discord, iMessage, Slack, Teams, Telegram, WhatsApp, and 20+ more, plus native apps for macOS, iOS, Android, Windows, and Linux. One Gateway runs it as a personal assistant on a laptop or as a shared team deployment; configuration is the only difference. Yours, with no catch. State, memory, and credentials live on your hardware. Models and agent harnesses (Claude, Codex, local models) are plugins you can swap without changing anything…
read the full OpenClaw overview →
About DeepAnalyze
DeepAnalyze: Agentic Large Language Models for Autonomous Data Science Authors : Shaolei Zhang, Ju Fan , Meihao Fan, Guoliang Li, Xiaoyong Du Renmin University of China, Tsinghua University DeepAnalyze is the first agentic LLM for autonomous data science. It can autonomously complete a wide range of data centric tasks without human intervention, supporting: 🛠 Entire data science pipeline : Automatically perform any data science tasks such as data preparation, analysis, modeling, visualization, and report generation. 🔍 Open ended data research : Conduct deep research on diverse data sources, including…
read the full DeepAnalyze overview →
More in AI & Machine Learning
Related comparisons
More AI Interaction & Interfaces projects
Compare either of these against the rest of the AI Interaction & Interfaces field.
Frequently asked questions
Is OpenClaw or DeepAnalyze more popular?
OpenClaw has 393,747 GitHub stars and DeepAnalyze has 4,769. OpenClaw has the larger community by that measure.
Are OpenClaw and DeepAnalyze free?
Both are open source. OpenClaw is licensed under MIT and DeepAnalyze under MIT. Neither carries a licence fee.
What is the difference between OpenClaw and DeepAnalyze?
OpenClaw is written in TypeScript and DeepAnalyze 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, OpenClaw or DeepAnalyze?
Choose OpenClaw if you want the larger community (393,747 stars) or its MIT licence terms. Choose DeepAnalyze if its feature set, stack or MIT licence fits better. Both are self-hostable.