--- title: "memfree vs mempalace" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/memfreeme-memfree-vs-mempalace-mempalace" tools: ["memfreeme-memfree", "mempalace-mempalace"] --- # memfree vs mempalace *GraphCanon updated Oct 4, 2026* ## Verdict Pick memfree if memfree; 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. [memfree](https://www.memfree.me?ref=github.com) reports 1.5k GitHub stars, 211 forks, and 19 open issues, last pushed Jul 6, 2026. [mempalace](http://mempalaceofficial.com/) has 59k stars, 7.6k forks, and 735 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [memfree's repository](https://github.com/memfreeme/memfree) and [mempalace's repository](https://github.com/MemPalace/mempalace). | | [memfree](/tools/memfreeme-memfree.md) | [mempalace](/tools/mempalace-mempalace.md) | | --- | --- | --- | | Tagline | Hybrid AI Search Engine & AI Page Generator | The best-benchmarked open-source AI memory system | | Stars | 1,505 | 59,143 | | Forks | 211 | 7,565 | | Open issues | 19 | 735 | | Language | TypeScript | Python | | Adopt for | memfree | 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. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [memfree](/tools/memfreeme-memfree.md) | [mempalace](/tools/mempalace-mempalace.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 62d | 0d | | Open issues (now) | 19 | 735 | | Stars delta | -3 (30d) | +743 (30d) | | Open issues delta | +2 (30d) | +31 (30d) | | Full report | [trust report](/tools/memfreeme-memfree/trust.md) | [trust report](/tools/mempalace-mempalace/trust.md) | ## Decision facts: memfree - **Pricing:** freemium - Open-Source under MIT License, but commercial support might come with additional costs - **Requirements:** Min 4 GB RAM; Requires Docker; Requires TypeScript for development or customization.; Best-suited for environments that can leverage serverless capabilities and React-based UI generation. - **Adopt for:** memfree ## 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. ## Choose when ### Choose memfree if… - memfree is primarily TypeScript; mempalace is Python. - Pricing: Open-Source under MIT License, but commercial support might come with additional costs. - Requirements: Min 4 GB RAM; Requires Docker; Requires TypeScript for development or customization.; Best-suited for environments that can leverage serverless capabilities and React-based UI generation.. - Tags unique to memfree: ai-search, hybrid-ai-search, page-generator, serverless-vector. - When you need a hybrid approach combining traditional indexing with vector-based searches for more efficient AI-powered querying. ### Choose mempalace if… - mempalace is primarily Python; memfree is TypeScript. - Tags unique to mempalace: ai, chromadb, embedding, llm. - 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 NOT to use memfree - When your requirements strictly demand pure vector database solutions without the aid of traditional indexing methods. - If you do not need an integrated page generator as part of your AI search capabilities. ## 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. ## Common questions ### What is the difference between memfree and mempalace? memfree: Hybrid AI Search Engine & AI Page Generator. mempalace: The best-benchmarked open-source AI memory system. See the comparison table for live GitHub stats and shared categories. ### When should I choose memfree over mempalace? Choose memfree over mempalace when memfree is primarily TypeScript; mempalace is Python; Pricing: Open-Source under MIT License, but commercial support might come with additional costs; Requirements: Min 4 GB RAM; Requires Docker; Requires TypeScript for development or customization.; Best-suited for environments that can leverage serverless capabilities and React-based UI generation.; Tags unique to memfree: ai-search, hybrid-ai-search, page-generator, serverless-vector; When you need a hybrid approach combining traditional indexing with vector-based searches for more efficient AI-powered querying. ### When should I choose mempalace over memfree? Choose mempalace over memfree when mempalace is primarily Python; memfree is TypeScript; Tags unique to mempalace: ai, chromadb, embedding, llm; 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 avoid memfree? When your requirements strictly demand pure vector database solutions without the aid of traditional indexing methods. If you do not need an integrated page generator as part of your AI search capabilities. ### 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. ### Is memfree or mempalace more popular on GitHub? mempalace has more GitHub stars (59,143 vs 1,505). Stars measure visibility, not whether either tool fits your constraints. ### Are memfree and mempalace open source? Yes - both are open-source projects on GitHub (memfree: MIT, mempalace: MIT). ### Where can I find alternatives to memfree or mempalace? GraphCanon lists graph-backed alternatives at [memfree alternatives](/tools/memfreeme-memfree/alternatives) and [mempalace alternatives](/tools/mempalace-mempalace/alternatives) ([memfree markdown twin](/tools/memfreeme-memfree/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/memfreeme-memfree-vs-mempalace-mempalace.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, memfree or mempalace? memfree: Steady. 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 memfree and mempalace? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [memfree trust report](/tools/memfreeme-memfree/trust); [mempalace trust report](/tools/mempalace-mempalace/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=memfreeme-memfree`](/api/graphcanon/graph?tool=memfreeme-memfree) - 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/_