--- title: "automem vs memsearch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/verygoodplugins-automem-vs-zilliztech-memsearch" tools: ["verygoodplugins-automem", "zilliztech-memsearch"] --- # automem vs memsearch *GraphCanon updated Aug 22, 2026* ## Verdict Pick automem if autoMem leverages both graph and vector database technologies to provide AI assistants with durable relational memory; pick memsearch if memsearch is a hybrid memory management solution for AI agents with Markdown and Milvus backing, ideal for rich semantic search and long-term data storage. [automem](https://automem.ai/) reports 802 GitHub stars, 102 forks, and 15 open issues, last pushed Aug 14, 2026. [memsearch](https://zilliztech.github.io/memsearch/) has 2.5k stars, 231 forks, and 240 open issues, last pushed Aug 21, 2026. Figures are from public GitHub metadata via [automem's repository](https://github.com/verygoodplugins/automem) and [memsearch's repository](https://github.com/zilliztech/memsearch). | | [automem](/tools/verygoodplugins-automem.md) | [memsearch](/tools/zilliztech-memsearch.md) | | --- | --- | --- | | Tagline | Graph-vector memory service for durable, relational AI assistant memory | A persistent, unified memory layer for all your AI agents backed by Markdown and Milvus. | | Stars | 802 | 2,491 | | Forks | 102 | 231 | | Open issues | 15 | 240 | | Language | Python | Python | | Adopt for | AutoMem leverages both graph and vector database technologies to provide AI assistants with durable relational memory. | memsearch is a hybrid memory management solution for AI agents with Markdown and Milvus backing, ideal for rich semantic search and long-term data storage. | | Persona | - | - | | Runtime | - | - | | License | AutoMem is licensed under the MIT License, which means it is free to use, modify, and distribute as long as license terms are met. | MIT | | Categories | AI Agents, Vector Databases | AI Agents, Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [automem](/tools/verygoodplugins-automem.md) | [memsearch](/tools/zilliztech-memsearch.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 7d | 0d | | Open issues (now) | 15 | 240 | | Stars delta | +9 (30d) | +155 (30d) | | Open issues delta | +4 (30d) | +9 (30d) | | Full report | [trust report](/tools/verygoodplugins-automem/trust.md) | [trust report](/tools/zilliztech-memsearch/trust.md) | ## 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. ## Decision facts: memsearch - **Adopt for:** memsearch is a hybrid memory management solution for AI agents with Markdown and Milvus backing, ideal for rich semantic search and long-term data storage. ## Choose when ### Choose automem if… - Pricing: Free for open-source use, with no explicit commercial licensing information provided.. - Tags unique to automem: ai-memory, anthropic, falkordb, graph-database. - automem ships Docker support for self-hosted deployment. - Use AutoMem when you need an AI assistant capable of maintaining rich, relational memories over time. ### Choose memsearch if… - Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search. - Also covers Data & Retrieval. - When you need robust integration with AI agents like Claude Code or Codex ## 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. ## When NOT to use memsearch - If your application doesn't require integration with specific AI agents like Claude Code - In cases where only simple text data storage without semantic search is needed ## Common questions ### What is the difference between automem and memsearch? automem: Graph-vector memory service for durable, relational AI assistant memory. memsearch: A persistent, unified memory layer for all your AI agents backed by Markdown and Milvus.. See the comparison table for live GitHub stats and shared categories. ### When should I choose automem over memsearch? Choose automem over memsearch when Pricing: Free for open-source use, with no explicit commercial licensing information provided.; Tags unique to automem: ai-memory, anthropic, falkordb, graph-database; 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 choose memsearch over automem? Choose memsearch over automem when Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search; Also covers Data & Retrieval; When you need robust integration with AI agents like Claude Code or Codex. ### 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. ### When should I avoid memsearch? If your application doesn't require integration with specific AI agents like Claude Code In cases where only simple text data storage without semantic search is needed ### Is automem or memsearch more popular on GitHub? memsearch has more GitHub stars (2,491 vs 802). Stars measure visibility, not whether either tool fits your constraints. ### Are automem and memsearch open source? Yes - both are open-source projects on GitHub (automem: MIT, memsearch: MIT). ### Where can I find alternatives to automem or memsearch? GraphCanon lists graph-backed alternatives at [automem alternatives](/tools/verygoodplugins-automem/alternatives) and [memsearch alternatives](/tools/zilliztech-memsearch/alternatives) ([automem markdown twin](/tools/verygoodplugins-automem/alternatives.md), [memsearch markdown twin](/tools/zilliztech-memsearch/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/verygoodplugins-automem-vs-zilliztech-memsearch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, automem or memsearch? automem: Active. memsearch: Very 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 automem and memsearch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [automem trust report](/tools/verygoodplugins-automem/trust); [memsearch trust report](/tools/zilliztech-memsearch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=verygoodplugins-automem`](/api/graphcanon/graph?tool=verygoodplugins-automem) - 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/_