--- title: "pmb vs automem" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/oleksiijko-pmb-vs-verygoodplugins-automem" tools: ["oleksiijko-pmb", "verygoodplugins-automem"] --- # pmb vs automem *GraphCanon updated Aug 23, 2026* ## Verdict Pick pmb if pmb - Local-first persistent memory for AI coding agents; pick automem if autoMem leverages both graph and vector database technologies to provide AI assistants with durable relational memory. [pmb](https://pypi.org/project/pmb-ai/) reports 295 GitHub stars, 23 forks, and 9 open issues, last pushed Aug 17, 2026. [automem](https://automem.ai/) has 802 stars, 102 forks, and 15 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [pmb's repository](https://github.com/oleksiijko/pmb) and [automem's repository](https://github.com/verygoodplugins/automem). | | [pmb](/tools/oleksiijko-pmb.md) | [automem](/tools/verygoodplugins-automem.md) | | --- | --- | --- | | Tagline | Local-first persistent memory for AI coding agents with offline and multilingual capabilities. | Graph-vector memory service for durable, relational AI assistant memory | | Stars | 295 | 802 | | Forks | 23 | 102 | | Open issues | 9 | 15 | | Language | Python | Python | | Adopt for | pmb - Local-first persistent memory for AI coding agents | AutoMem leverages both graph and vector database technologies to provide AI assistants with durable relational memory. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | AutoMem is licensed under the MIT License, which means it is free to use, modify, and distribute as long as license terms are met. | | Categories | AI Agents, Data & Retrieval | AI Agents, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [pmb](/tools/oleksiijko-pmb.md) | [automem](/tools/verygoodplugins-automem.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 6d | 7d | | Open issues (now) | 9 | 15 | | Stars delta | +16 (30d) | +9 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/oleksiijko-pmb/trust.md) | [trust report](/tools/verygoodplugins-automem/trust.md) | ## Decision facts: pmb - **Requirements:** No explicit requirements listed in repository data, but likely Python and compatible SQL database setup. - **Adopt for:** pmb - Local-first persistent memory for AI coding agents - **License detail:** Apache-2.0 ## Decision facts: automem - **Pricing:** freemium - Free for open-source use, with no explicit commercial licensing information provided. - **Adopt for:** AutoMem leverages both graph and vector database technologies to provide AI assistants with durable relational memory. - **License detail:** AutoMem is licensed under the MIT License, which means it is free to use, modify, and distribute as long as license terms are met. ## Choose when ### Choose pmb if… - License: pmb is Apache-2.0, automem is MIT. - Requirements: No explicit requirements listed in repository data, but likely Python and compatible SQL database setup.. - Tags unique to pmb: ai-agents, bm25, claude-code, codex. - Also covers Data & Retrieval. - - When you need a solution that integrates directly with popular AI coding agents such as Claude Code, Cursor, and Codex. ### Choose automem if… - License: automem is MIT, pmb is Apache-2.0. - Pricing: Free for open-source use, with no explicit commercial licensing information provided.. - Tags unique to automem: anthropic, falkordb, graph-database, llm. - Also covers Vector Databases. - automem ships Docker support for self-hosted deployment. - Use AutoMem when you need an AI assistant capable of maintaining rich, relational memories over time. ## When NOT to use pmb - - In scenarios where real-time data retrieval is essential since pmb focuses on local storage rather than cloud-based synchronization. - - If your project requires heavy reliance on online services or if offline functionality doesn't provide a necessary advantage. - - When the specific use case does not benefit from having multilingual capabilities for AI coding tasks. ## When NOT to use automem - Avoid using AutoMem if your application does not benefit from persistent memory or relational context, as it might add unnecessary overhead. - If you require a simpler key-value storage system for less complex or non-relational data, AutoMem's graph and vector capabilities may be overkill. ## Common questions ### What is the difference between pmb and automem? pmb: Local-first persistent memory for AI coding agents with offline and multilingual capabilities.. automem: Graph-vector memory service for durable, relational AI assistant memory. See the comparison table for live GitHub stats and shared categories. ### When should I choose pmb over automem? Choose pmb over automem when License: pmb is Apache-2.0, automem is MIT; Requirements: No explicit requirements listed in repository data, but likely Python and compatible SQL database setup.; Tags unique to pmb: ai-agents, bm25, claude-code, codex; Also covers Data & Retrieval; - When you need a solution that integrates directly with popular AI coding agents such as Claude Code, Cursor, and Codex. ### When should I choose automem over pmb? Choose automem over pmb when License: automem is MIT, pmb is Apache-2.0; Pricing: Free for open-source use, with no explicit commercial licensing information provided.; Tags unique to automem: anthropic, falkordb, graph-database, llm; Also covers Vector Databases; automem ships Docker support for self-hosted deployment; Use AutoMem when you need an AI assistant capable of maintaining rich, relational memories over time. ### When should I avoid pmb? - In scenarios where real-time data retrieval is essential since pmb focuses on local storage rather than cloud-based synchronization. - If your project requires heavy reliance on online services or if offline functionality doesn't provide a necessary advantage. - When the specific use case does not benefit from having multilingual capabilities for AI coding tasks. ### When should I avoid automem? Avoid using AutoMem if your application does not benefit from persistent memory or relational context, as it might add unnecessary overhead. If you require a simpler key-value storage system for less complex or non-relational data, AutoMem's graph and vector capabilities may be overkill. ### Is pmb or automem more popular on GitHub? automem has more GitHub stars (802 vs 295). Stars measure visibility, not whether either tool fits your constraints. ### Are pmb and automem open source? Yes - both are open-source projects on GitHub (pmb: Apache-2.0, automem: MIT). ### Where can I find alternatives to pmb or automem? GraphCanon lists graph-backed alternatives at [pmb alternatives](/tools/oleksiijko-pmb/alternatives) and [automem alternatives](/tools/verygoodplugins-automem/alternatives) ([pmb markdown twin](/tools/oleksiijko-pmb/alternatives.md), [automem markdown twin](/tools/verygoodplugins-automem/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/oleksiijko-pmb-vs-verygoodplugins-automem.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, pmb or automem? pmb: Very active. automem: 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 pmb and automem? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [pmb trust report](/tools/oleksiijko-pmb/trust); [automem trust report](/tools/verygoodplugins-automem/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=oleksiijko-pmb`](/api/graphcanon/graph?tool=oleksiijko-pmb) - 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/_