--- title: "TencentDB-Agent-Memory vs deep-searcher" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/tencentcloud-tencentdb-agent-memory-vs-zilliztech-deep-searcher" tools: ["tencentcloud-tencentdb-agent-memory", "zilliztech-deep-searcher"] --- # TencentDB-Agent-Memory vs deep-searcher *GraphCanon updated Jul 12, 2026* ## Verdict Pick TencentDB-Agent-Memory when tencentDB-Agent-Memory is primarily TypeScript; deep-searcher is Python; pick deep-searcher when deep-searcher is primarily Python; TencentDB-Agent-Memory is TypeScript. [TencentDB-Agent-Memory](https://github.com/TencentCloud/TencentDB-Agent-Memory) reports 8.4k GitHub stars, 772 forks, and 257 open issues, last pushed Jun 26, 2026. [deep-searcher](https://zilliztech.github.io/deep-searcher/) has 7.9k stars, 768 forks, and 53 open issues, last pushed Nov 19, 2025. Figures are from public GitHub metadata via [TencentDB-Agent-Memory's repository](https://github.com/TencentCloud/TencentDB-Agent-Memory) and [deep-searcher's repository](https://github.com/zilliztech/deep-searcher). | | [TencentDB-Agent-Memory](/tools/tencentcloud-tencentdb-agent-memory.md) | [deep-searcher](/tools/zilliztech-deep-searcher.md) | | --- | --- | --- | | Tagline | TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies. | Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python. | | Stars | 8,404 | 7,941 | | Forks | 772 | 768 | | Open issues | 257 | 53 | | Language | TypeScript | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | LLM Frameworks, AI Agents, Vector Databases | LLM Frameworks, Vector Databases, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [TencentDB-Agent-Memory](/tools/tencentcloud-tencentdb-agent-memory.md) | [deep-searcher](/tools/zilliztech-deep-searcher.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 15d | 234d | | Open issues (now) | 257 | 53 | | Full report | [trust report](/tools/tencentcloud-tencentdb-agent-memory/trust.md) | [trust report](/tools/zilliztech-deep-searcher/trust.md) | ## Decision facts: deep-searcher - **Pricing:** freemium ## Choose when ### Choose TencentDB-Agent-Memory if… - TencentDB-Agent-Memory is primarily TypeScript; deep-searcher is Python. - License: TencentDB-Agent-Memory is Other, deep-searcher is Apache-2.0. - Tags unique to TencentDB-Agent-Memory: memory, llm, local-first, openclaw-plugin. ### Choose deep-searcher if… - deep-searcher is primarily Python; TencentDB-Agent-Memory is TypeScript. - License: deep-searcher is Apache-2.0, TencentDB-Agent-Memory is Other. - Tags unique to deep-searcher: grok, deepseek-r1, deepseek, claude. - deep-searcher ships Docker support for self-hosted deployment. - - When you need an open-source alternative for reasoning and searching on private data, avoiding closed systems like Claude or Grok. ## When NOT to use TencentDB-Agent-Memory - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use deep-searcher - - If you need a tool that supports web crawling out-of-the-box, as DeepSearcher currently lacks this feature, although it is on their future plans. - - When your project prioritizes using specific vector databases other than Milvus; while there are future plans to support more, these are not yet implemented. - - For rapid setup without additional configuration or dependency management; DeepSearcher requires detailed setup and optional dependencies for full functionality. ## Common questions ### What is the difference between TencentDB-Agent-Memory and deep-searcher? TencentDB-Agent-Memory: TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.. deep-searcher: Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.. See the comparison table for live GitHub stats and shared categories. ### When should I choose TencentDB-Agent-Memory over deep-searcher? Choose TencentDB-Agent-Memory over deep-searcher when TencentDB-Agent-Memory is primarily TypeScript; deep-searcher is Python; License: TencentDB-Agent-Memory is Other, deep-searcher is Apache-2.0; Tags unique to TencentDB-Agent-Memory: memory, llm, local-first, openclaw-plugin. ### When should I choose deep-searcher over TencentDB-Agent-Memory? Choose deep-searcher over TencentDB-Agent-Memory when deep-searcher is primarily Python; TencentDB-Agent-Memory is TypeScript; License: deep-searcher is Apache-2.0, TencentDB-Agent-Memory is Other; Tags unique to deep-searcher: grok, deepseek-r1, deepseek, claude; deep-searcher ships Docker support for self-hosted deployment; - When you need an open-source alternative for reasoning and searching on private data, avoiding closed systems like Claude or Grok. ### When should I avoid TencentDB-Agent-Memory? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid deep-searcher? - If you need a tool that supports web crawling out-of-the-box, as DeepSearcher currently lacks this feature, although it is on their future plans. - When your project prioritizes using specific vector databases other than Milvus; while there are future plans to support more, these are not yet implemented. - For rapid setup without additional configuration or dependency management; DeepSearcher requires detailed setup and optional dependencies for full functionality. ### Is TencentDB-Agent-Memory or deep-searcher more popular on GitHub? TencentDB-Agent-Memory has more GitHub stars (8,404 vs 7,941). Stars measure visibility, not whether either tool fits your constraints. ### Are TencentDB-Agent-Memory and deep-searcher open source? Yes - both are open-source projects on GitHub (TencentDB-Agent-Memory: Other, deep-searcher: Apache-2.0). ### Where can I find alternatives to TencentDB-Agent-Memory or deep-searcher? GraphCanon lists graph-backed alternatives at [TencentDB-Agent-Memory alternatives](/tools/tencentcloud-tencentdb-agent-memory/alternatives) and [deep-searcher alternatives](/tools/zilliztech-deep-searcher/alternatives) ([TencentDB-Agent-Memory markdown twin](/tools/tencentcloud-tencentdb-agent-memory/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/tencentcloud-tencentdb-agent-memory-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, TencentDB-Agent-Memory or deep-searcher? TencentDB-Agent-Memory: 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 TencentDB-Agent-Memory and deep-searcher? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [TencentDB-Agent-Memory trust report](/tools/tencentcloud-tencentdb-agent-memory/trust); [deep-searcher trust report](/tools/zilliztech-deep-searcher/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=tencentcloud-tencentdb-agent-memory`](/api/graphcanon/graph?tool=tencentcloud-tencentdb-agent-memory) - 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/_