--- title: "Memori vs mempalace" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/memorilabs-memori-vs-mempalace-mempalace" tools: ["memorilabs-memori", "mempalace-mempalace"] --- # Memori vs mempalace *GraphCanon updated Jul 17, 2026* ## Verdict Pick Memori if memori is an agent-native memory infrastructure layer that converts agent execution and conversation into a structured, persistent state for use in production systems. It supports various deployment environments such as云; pick mempalace if memPalace is an advanced open-source AI memory system that integrates with ChromaDB to optimize machine learning model memories and enhance data retrieval efficiency. [Memori](https://memorilabs.ai) reports 16k GitHub stars, 2.8k forks, and 23 open issues, last pushed Jun 15, 2026. [mempalace](http://mempalaceofficial.com/) has 57k stars, 7.4k forks, and 627 open issues, last pushed Jul 16, 2026. Figures are from public GitHub metadata via [Memori's repository](https://github.com/MemoriLabs/Memori) and [mempalace's repository](https://github.com/MemPalace/mempalace). | | [Memori](/tools/memorilabs-memori.md) | [mempalace](/tools/mempalace-mempalace.md) | | --- | --- | --- | | Tagline | Agent-native memory infrastructure for LLM systems | The best-benchmarked open-source AI memory system. | | Stars | 15,570 | 57,399 | | Forks | 2,802 | 7,399 | | Open issues | 23 | 627 | | Language | Python | Python | | Adopt for | Memori is an agent-native memory infrastructure layer that converts agent execution and conversation into a structured, persistent state for use in production systems. It supports various deployment environments such as云 | MemPalace is an advanced open-source AI memory system that integrates with ChromaDB to optimize machine learning model memories and enhance data retrieval efficiency. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | AI Agents, Data & Retrieval | Model Training, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Memori](/tools/memorilabs-memori.md) | [mempalace](/tools/mempalace-mempalace.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 25d | 0d | | Open issues (now) | 23 | 627 | | Full report | [trust report](/tools/memorilabs-memori/trust.md) | [trust report](/tools/mempalace-mempalace/trust.md) | **Typed relationship:** Memori _(alternative)_ mempalace MemPalace and Memori both provide memory infrastructure for LLM systems but with different design focuses (benchmarking & open-source vs agent-native memory). ## Shared compatibility - **Python**: [Memori](/tools/memorilabs-memori.md) - Python runtime; [mempalace](/tools/mempalace-mempalace.md) - Python runtime ## Decision facts: Memori - **Adopt for:** Memori is an agent-native memory infrastructure layer that converts agent execution and conversation into a structured, persistent state for use in production systems. It supports various deployment environments such as云 ## Decision facts: mempalace - **Adopt for:** MemPalace is an advanced open-source AI memory system that integrates with ChromaDB to optimize machine learning model memories and enhance data retrieval efficiency. ## Choose when ### Choose Memori if… - License: Memori is Other, mempalace is MIT. - MemPalace and Memori both provide memory infrastructure for LLM systems but with different design focuses (benchmarking & open-source vs agent-native memory). - Tags unique to Memori: agent-memory, enterprise, memory-management, python. - Also covers AI Agents, Data & Retrieval. - 您需要一个可以在多种部署环境中工作的内存基础设施，包括云端和本地环境时。 ### Choose mempalace if… - License: mempalace is MIT, Memori is Other. - MemPalace and Memori both provide memory infrastructure for LLM systems but with different design focuses (benchmarking & open-source vs agent-native memory). - Tags unique to mempalace: ai, chromadb, memory. - Also covers Model Training, Vector Databases. - When you need a highly benchmarked solution for managing AI model memories, MemPalace can provide superior performance due to its optimization features integrated specifically around ML model needs. ## When NOT to use Memori - （TypeScriptPython），MemoriSDK。 ## When NOT to use mempalace - Avoid if requiring a proprietary system where full transparency or customization of the memory management layer may not be necessary, since MemPalace is open source and might involve deeper technical - If your project strictly adheres to non-MIT licenses, then MemPalace might not be suitable due to its MIT license which may conflict with licensing requirements. ## Common questions ### What is the difference between Memori and mempalace? Memori: Agent-native memory infrastructure for LLM systems. mempalace: The best-benchmarked open-source AI memory system.. See the comparison table for live GitHub stats and shared categories. ### When should I choose Memori over mempalace? Choose Memori over mempalace when License: Memori is Other, mempalace is MIT; MemPalace and Memori both provide memory infrastructure for LLM systems but with different design focuses (benchmarking & open-source vs agent-native memory); Tags unique to Memori: agent-memory, enterprise, memory-management, python; Also covers AI Agents, Data & Retrieval; 您需要一个可以在多种部署环境中工作的内存基础设施，包括云端和本地环境时。. ### When should I choose mempalace over Memori? Choose mempalace over Memori when License: mempalace is MIT, Memori is Other; MemPalace and Memori both provide memory infrastructure for LLM systems but with different design focuses (benchmarking & open-source vs agent-native memory); Tags unique to mempalace: ai, chromadb, memory; Also covers Model Training, Vector Databases; When you need a highly benchmarked solution for managing AI model memories, MemPalace can provide superior performance due to its optimization features integrated specifically around ML model needs. ### When should I avoid Memori? （TypeScriptPython），MemoriSDK。 ### When should I avoid mempalace? Avoid if requiring a proprietary system where full transparency or customization of the memory management layer may not be necessary, since MemPalace is open source and might involve deeper technical If your project strictly adheres to non-MIT licenses, then MemPalace might not be suitable due to its MIT license which may conflict with licensing requirements. ### Is Memori or mempalace more popular on GitHub? mempalace has more GitHub stars (57,399 vs 15,570). Stars measure visibility, not whether either tool fits your constraints. ### Are Memori and mempalace open source? Yes - both are open-source projects on GitHub (Memori: Other, mempalace: MIT). ### Where can I find alternatives to Memori or mempalace? GraphCanon lists graph-backed alternatives at [Memori alternatives](/tools/memorilabs-memori/alternatives) and [mempalace alternatives](/tools/mempalace-mempalace/alternatives) ([Memori markdown twin](/tools/memorilabs-memori/alternatives.md), [mempalace markdown twin](/tools/mempalace-mempalace/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/memorilabs-memori-vs-mempalace-mempalace.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Memori or mempalace? Memori: Active. mempalace: 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 Memori and mempalace? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Memori trust report](/tools/memorilabs-memori/trust); [mempalace trust report](/tools/mempalace-mempalace/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=memorilabs-memori`](/api/graphcanon/graph?tool=memorilabs-memori) - 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/_