--- title: "mempalace vs NeumAI" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mempalace-mempalace-vs-neumtry-neumai" tools: ["mempalace-mempalace", "neumtry-neumai"] --- # mempalace vs NeumAI *GraphCanon updated Oct 4, 2026* ## Verdict Pick mempalace if mempalace is an open-source AI memory system that leverages ChromaDB as its default vector-store backend, supporting Python 3.9+ and offering both local and server-based embedding options; pick NeumAI if neumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with. [mempalace](http://mempalaceofficial.com/) reports 59k GitHub stars, 7.6k forks, and 735 open issues, last pushed Sep 18, 2026. [NeumAI](https://neum.ai) has 869 stars, 50 forks, and 9 open issues, last pushed Jan 15, 2024. Figures are from public GitHub metadata via [mempalace's repository](https://github.com/MemPalace/mempalace) and [NeumAI's repository](https://github.com/NeumTry/NeumAI). | | [mempalace](/tools/mempalace-mempalace.md) | [NeumAI](/tools/neumtry-neumai.md) | | --- | --- | --- | | Tagline | The best-benchmarked open-source AI memory system | Framework to manage creation and synchronization of vector embeddings at large scale | | Stars | 59,143 | 869 | | Forks | 7,565 | 50 | | Open issues | 735 | 9 | | Language | Python | Python | | Adopt for | mempalace is an open-source AI memory system that leverages ChromaDB as its default vector-store backend, supporting Python 3.9+ and offering both local and server-based embedding options. | NeumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with an open | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mempalace](/tools/mempalace-mempalace.md) | [NeumAI](/tools/neumtry-neumai.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 978d | | Open issues (now) | 735 | 9 | | Stars delta | +743 (30d) | +2 (30d) | | Open issues delta | +31 (30d) | 0 (30d) | | Full report | [trust report](/tools/mempalace-mempalace/trust.md) | [trust report](/tools/neumtry-neumai/trust.md) | ## Decision facts: mempalace - **Adopt for:** mempalace is an open-source AI memory system that leverages ChromaDB as its default vector-store backend, supporting Python 3.9+ and offering both local and server-based embedding options. ## Decision facts: NeumAI - **Pricing:** freemium - Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options. - **Requirements:** Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting. - **Adopt for:** NeumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with an open ## Choose when ### Choose mempalace if… - License: mempalace is MIT, NeumAI is Apache-2.0. - Tags unique to mempalace: chromadb, embedding, llm, mcp. - mempalace ships Docker support for self-hosted deployment. - When you need a benchmarked open-source AI memory system that supports a wide range of languages through the embeddinggemma-300m model. ### Choose NeumAI if… - License: NeumAI is Apache-2.0, mempalace is MIT. - Pricing: Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options.. - Requirements: Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting.. - Tags unique to NeumAI: data-engineering, database, embeddings, etl. - When you require robust and scalable infrastructure specifically designed for creating and synchronizing vector embeddings at scale. ## When NOT to use mempalace - If you are working in an environment where Python 3.9+ is not available, as mempalace requires this version or higher. - When you need a system that does not require at least 300 MB of disk space for the embedding model, as mempalace requires this minimum space for its recommended multilingual model. ## When NOT to use NeumAI - When your project requires customization beyond what the provided architecture allows, without the support expected from commercial offerings or competitive open-source frameworks. - If your needs are simpler and don't demand large-scale operations, NeumAI’s capabilities focused on handling vast vector sets may be excessive for smaller projects. ## Common questions ### What is the difference between mempalace and NeumAI? mempalace: The best-benchmarked open-source AI memory system. NeumAI: Framework to manage creation and synchronization of vector embeddings at large scale. See the comparison table for live GitHub stats and shared categories. ### When should I choose mempalace over NeumAI? Choose mempalace over NeumAI when License: mempalace is MIT, NeumAI is Apache-2.0; Tags unique to mempalace: chromadb, embedding, llm, mcp; mempalace ships Docker support for self-hosted deployment; When you need a benchmarked open-source AI memory system that supports a wide range of languages through the embeddinggemma-300m model. ### When should I choose NeumAI over mempalace? Choose NeumAI over mempalace when License: NeumAI is Apache-2.0, mempalace is MIT; Pricing: Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options.; Requirements: Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting.; Tags unique to NeumAI: data-engineering, database, embeddings, etl; When you require robust and scalable infrastructure specifically designed for creating and synchronizing vector embeddings at scale. ### When should I avoid mempalace? If you are working in an environment where Python 3.9+ is not available, as mempalace requires this version or higher. When you need a system that does not require at least 300 MB of disk space for the embedding model, as mempalace requires this minimum space for its recommended multilingual model. ### When should I avoid NeumAI? When your project requires customization beyond what the provided architecture allows, without the support expected from commercial offerings or competitive open-source frameworks. If your needs are simpler and don't demand large-scale operations, NeumAI’s capabilities focused on handling vast vector sets may be excessive for smaller projects. ### Is mempalace or NeumAI more popular on GitHub? mempalace has more GitHub stars (59,143 vs 869). Stars measure visibility, not whether either tool fits your constraints. ### Are mempalace and NeumAI open source? Yes - both are open-source projects on GitHub (mempalace: MIT, NeumAI: Apache-2.0). ### Where can I find alternatives to mempalace or NeumAI? GraphCanon lists graph-backed alternatives at [mempalace alternatives](/tools/mempalace-mempalace/alternatives) and [NeumAI alternatives](/tools/neumtry-neumai/alternatives) ([mempalace markdown twin](/tools/mempalace-mempalace/alternatives.md), [NeumAI markdown twin](/tools/neumtry-neumai/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/mempalace-mempalace-vs-neumtry-neumai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mempalace or NeumAI? mempalace: Very active. NeumAI: Dormant. 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 mempalace and NeumAI? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mempalace trust report](/tools/mempalace-mempalace/trust); [NeumAI trust report](/tools/neumtry-neumai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mempalace-mempalace`](/api/graphcanon/graph?tool=mempalace-mempalace) - 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/_