--- title: "synto vs deep-searcher" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kytmanov-synto-vs-zilliztech-deep-searcher" tools: ["kytmanov-synto", "zilliztech-deep-searcher"] --- # synto vs deep-searcher *GraphCanon updated Sep 20, 2026* ## Verdict Pick synto if synto is an AI-powered markdown note management system for Obsidian users who prioritize local-first operations and personal knowledge management with zero online data sharing; pick deep-searcher if deepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license. [synto](https://github.com/kytmanov/synto) reports 255 GitHub stars, 25 forks, and 10 open issues, last pushed Sep 2, 2026. [deep-searcher](https://zilliztech.github.io/deep-searcher/) has 8.1k stars, 775 forks, and 53 open issues, last pushed Nov 19, 2025. Figures are from public GitHub metadata via [synto's repository](https://github.com/kytmanov/synto) and [deep-searcher's repository](https://github.com/zilliztech/deep-searcher). | | [synto](/tools/kytmanov-synto.md) | [deep-searcher](/tools/zilliztech-deep-searcher.md) | | --- | --- | --- | | Tagline | Local AI-powered markdown note management system for Obsidian | Open Source Deep Research Alternative to Reason and Search on Private Data. | | Stars | 255 | 8,060 | | Forks | 25 | 775 | | Open issues | 10 | 53 | | Language | Python | Python | | Adopt for | Synto is an AI-powered markdown note management system for Obsidian users who prioritize local-first operations and personal knowledge management with zero online data sharing. | DeepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Developer Tools, LLM Frameworks | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [synto](/tools/kytmanov-synto.md) | [deep-searcher](/tools/zilliztech-deep-searcher.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 17d | 272d | | Open issues (now) | 10 | 53 | | Stars delta | +25 (30d) | +59 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/kytmanov-synto/trust.md) | [trust report](/tools/zilliztech-deep-searcher/trust.md) | ## Shared compatibility - **Python**: [synto](/tools/kytmanov-synto.md) - Python runtime; [deep-searcher](/tools/zilliztech-deep-searcher.md) - Python runtime ## Decision facts: synto - **Pricing:** freemium - **Requirements:** Min 2 GB RAM - **Adopt for:** Synto is an AI-powered markdown note management system for Obsidian users who prioritize local-first operations and personal knowledge management with zero online data sharing. - **License detail:** MIT ## Decision facts: deep-searcher - **Adopt for:** DeepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license. ## Choose when ### Choose synto if… - License: synto is MIT, deep-searcher is Apache-2.0. - Requirements: Min 2 GB RAM. - Tags unique to synto: git-based-wiki, knowledge-base, llm-knowledge-base, llm-tools. - Also covers Developer Tools. - When you prefer to keep all your personal notes and insights strictly on your device without any cloud involvement. ### Choose deep-searcher if… - License: deep-searcher is Apache-2.0, synto is MIT. - Tags unique to deep-searcher: agent, agentic-rag, deep-research, llm. - Also covers AI Agents, Vector Databases. - deep-searcher ships Docker support for self-hosted deployment. - When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3. ## When NOT to use synto - When you need cloud-based backup or sharing features across devices that support collaborative editing off-site. - If your workflow requires real-time synchronization and collaboration capabilities beyond a single device environment. - For teams looking to integrate their Obsidian wikis with external knowledge bases, as Synto focuses solely on local data. ## When NOT to use deep-searcher - Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems. - Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily. ## Common questions ### What is the difference between synto and deep-searcher? synto: Local AI-powered markdown note management system for Obsidian. deep-searcher: Open Source Deep Research Alternative to Reason and Search on Private Data.. See the comparison table for live GitHub stats and shared categories. ### When should I choose synto over deep-searcher? Choose synto over deep-searcher when License: synto is MIT, deep-searcher is Apache-2.0; Requirements: Min 2 GB RAM; Tags unique to synto: git-based-wiki, knowledge-base, llm-knowledge-base, llm-tools; Also covers Developer Tools; When you prefer to keep all your personal notes and insights strictly on your device without any cloud involvement. ### When should I choose deep-searcher over synto? Choose deep-searcher over synto when License: deep-searcher is Apache-2.0, synto is MIT; Tags unique to deep-searcher: agent, agentic-rag, deep-research, llm; Also covers AI Agents, Vector Databases; deep-searcher ships Docker support for self-hosted deployment; When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3. ### When should I avoid synto? When you need cloud-based backup or sharing features across devices that support collaborative editing off-site. If your workflow requires real-time synchronization and collaboration capabilities beyond a single device environment. For teams looking to integrate their Obsidian wikis with external knowledge bases, as Synto focuses solely on local data. ### When should I avoid deep-searcher? Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems. Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily. ### Is synto or deep-searcher more popular on GitHub? deep-searcher has more GitHub stars (8,060 vs 255). Stars measure visibility, not whether either tool fits your constraints. ### Are synto and deep-searcher open source? Yes - both are open-source projects on GitHub (synto: MIT, deep-searcher: Apache-2.0). ### Where can I find alternatives to synto or deep-searcher? GraphCanon lists graph-backed alternatives at [synto alternatives](/tools/kytmanov-synto/alternatives) and [deep-searcher alternatives](/tools/zilliztech-deep-searcher/alternatives) ([synto markdown twin](/tools/kytmanov-synto/alternatives.md), [deep-searcher markdown twin](/tools/zilliztech-deep-searcher/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/kytmanov-synto-vs-zilliztech-deep-searcher.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, synto or deep-searcher? synto: Active. deep-searcher: Slowing. 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 synto and deep-searcher? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [synto trust report](/tools/kytmanov-synto/trust); [deep-searcher trust report](/tools/zilliztech-deep-searcher/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kytmanov-synto`](/api/graphcanon/graph?tool=kytmanov-synto) - 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/_