--- title: "honcho vs TencentDB-Agent-Memory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/plastic-labs-honcho-vs-tencentcloud-tencentdb-agent-memory" tools: ["plastic-labs-honcho", "tencentcloud-tencentdb-agent-memory"] --- # honcho vs TencentDB-Agent-Memory *GraphCanon updated Jul 12, 2026* ## Verdict Pick honcho when honcho is primarily Python; TencentDB-Agent-Memory is TypeScript; pick TencentDB-Agent-Memory when tencentDB-Agent-Memory is primarily TypeScript; honcho is Python. [honcho](https://docs.honcho.dev) reports 5.9k GitHub stars, 707 forks, and 161 open issues, last pushed Jul 10, 2026. [TencentDB-Agent-Memory](https://github.com/TencentCloud/TencentDB-Agent-Memory) has 8.4k stars, 772 forks, and 257 open issues, last pushed Jun 26, 2026. Figures are from public GitHub metadata via [honcho's repository](https://github.com/plastic-labs/honcho) and [TencentDB-Agent-Memory's repository](https://github.com/TencentCloud/TencentDB-Agent-Memory). | | [honcho](/tools/plastic-labs-honcho.md) | [TencentDB-Agent-Memory](/tools/tencentcloud-tencentdb-agent-memory.md) | | --- | --- | --- | | Tagline | Memory library for building stateful agents | TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies. | | Stars | 5,902 | 8,404 | | Forks | 707 | 772 | | Open issues | 161 | 257 | | Language | Python | TypeScript | | Adopt for | A Python memory library designed for building stateful AI agents with a focus on long-term and contextual memory management. | - | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0: The software is free to use, distribute, and modify but requires that derivative works be similarly distributed as AGPL-3.0 under the same license. | Other | | Categories | AI Agents, LLM Frameworks, Vector Databases | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [honcho](/tools/plastic-labs-honcho.md) | [TencentDB-Agent-Memory](/tools/tencentcloud-tencentdb-agent-memory.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 15d | | Open issues (now) | 161 | 257 | | Full report | [trust report](/tools/plastic-labs-honcho/trust.md) | [trust report](/tools/tencentcloud-tencentdb-agent-memory/trust.md) | ## Decision facts: honcho - **Hosting:** self hosted - Honcho can be run locally using Docker, allowing for full control over the environment where it operates. - **Requirements:** - Requires setting up LLM API keys (Gemini, Anthropic, OpenAI) for certain functionalities.; - Python SDK needs to point to `http://localhost:8000` after Docker setup. - **Adopt for:** A Python memory library designed for building stateful AI agents with a focus on long-term and contextual memory management. - **License detail:** AGPL-3.0: The software is free to use, distribute, and modify but requires that derivative works be similarly distributed as AGPL-3.0 under the same license. ## Choose when ### Choose honcho if… - honcho is primarily Python; TencentDB-Agent-Memory is TypeScript. - License: honcho is AGPL-3.0, TencentDB-Agent-Memory is Other. - Honcho can be run locally using Docker, allowing for full control over the environment where it operates. - Requirements: - Requires setting up LLM API keys (Gemini, Anthropic, OpenAI) for certain functionalities.; - Python SDK needs to point to `http://localhost:8000` after Docker setup.. - Tags unique to honcho: agent-memory, ai, ai-agents, ai-memory. - honcho ships Docker support for self-hosted deployment. - - You are developing stateful AI agents that require robust, contextual, and long-term memory capabilities. ### Choose TencentDB-Agent-Memory if… - TencentDB-Agent-Memory is primarily TypeScript; honcho is Python. - License: TencentDB-Agent-Memory is Other, honcho is AGPL-3.0. - Tags unique to TencentDB-Agent-Memory: agent, ai-agent, embedding, llm. ## When NOT to use honcho - - If your use case does not require long-term or contextual memory management, as honcho might introduce unnecessary complexity. - - In scenarios where a proprietary license is required, given honcho's AGPL-3.0 license may have implications for open-sourcing modifications. ## When NOT to use TencentDB-Agent-Memory - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between honcho and TencentDB-Agent-Memory? honcho: Memory library for building stateful agents. 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.. See the comparison table for live GitHub stats and shared categories. ### When should I choose honcho over TencentDB-Agent-Memory? Choose honcho over TencentDB-Agent-Memory when honcho is primarily Python; TencentDB-Agent-Memory is TypeScript; License: honcho is AGPL-3.0, TencentDB-Agent-Memory is Other; Honcho can be run locally using Docker, allowing for full control over the environment where it operates; Requirements: - Requires setting up LLM API keys (Gemini, Anthropic, OpenAI) for certain functionalities.; - Python SDK needs to point to `http://localhost:8000` after Docker setup.; Tags unique to honcho: agent-memory, ai, ai-agents, ai-memory; honcho ships Docker support for self-hosted deployment; - You are developing stateful AI agents that require robust, contextual, and long-term memory capabilities. ### When should I choose TencentDB-Agent-Memory over honcho? Choose TencentDB-Agent-Memory over honcho when TencentDB-Agent-Memory is primarily TypeScript; honcho is Python; License: TencentDB-Agent-Memory is Other, honcho is AGPL-3.0; Tags unique to TencentDB-Agent-Memory: agent, ai-agent, embedding, llm. ### When should I avoid honcho? - If your use case does not require long-term or contextual memory management, as honcho might introduce unnecessary complexity. - In scenarios where a proprietary license is required, given honcho's AGPL-3.0 license may have implications for open-sourcing modifications. ### When should I avoid TencentDB-Agent-Memory? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is honcho or TencentDB-Agent-Memory more popular on GitHub? TencentDB-Agent-Memory has more GitHub stars (8,404 vs 5,902). Stars measure visibility, not whether either tool fits your constraints. ### Are honcho and TencentDB-Agent-Memory open source? Yes - both are open-source projects on GitHub (honcho: AGPL-3.0, TencentDB-Agent-Memory: Other). ### Where can I find alternatives to honcho or TencentDB-Agent-Memory? GraphCanon lists graph-backed alternatives at [honcho alternatives](/tools/plastic-labs-honcho/alternatives) and [TencentDB-Agent-Memory alternatives](/tools/tencentcloud-tencentdb-agent-memory/alternatives) ([honcho markdown twin](/tools/plastic-labs-honcho/alternatives.md), [TencentDB-Agent-Memory markdown twin](/tools/tencentcloud-tencentdb-agent-memory/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/plastic-labs-honcho-vs-tencentcloud-tencentdb-agent-memory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, honcho or TencentDB-Agent-Memory? honcho: Very active. TencentDB-Agent-Memory: 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 honcho and TencentDB-Agent-Memory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [honcho trust report](/tools/plastic-labs-honcho/trust); [TencentDB-Agent-Memory trust report](/tools/tencentcloud-tencentdb-agent-memory/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=plastic-labs-honcho`](/api/graphcanon/graph?tool=plastic-labs-honcho) - 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/_