Comparison
Memori vs mempalace
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 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.
Markdown twin · Memori alternatives · mempalace alternatives
GraphCanon updated Oct 4, 2026
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Trust & integrity
| Signal | Memori | mempalace |
|---|---|---|
| Maintenance | Very active (0d since push) As of Aug 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Oct 4, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Memori
- Agent-native memory infrastructure for LLM systems
- mempalace
- The best-benchmarked open-source AI memory system
Stars
- Memori
- 16k
- mempalace
- 59k
Forks
- Memori
- 3.2k
- mempalace
- 7.6k
Open issues
- Memori
- 33
- mempalace
- 735
Language
- Memori
- Python
- mempalace
- Python
Adopt for
- Memori
- 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
- 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
- Memori
- -
- mempalace
- -
Runtime
- Memori
- -
- mempalace
- -
License
- Memori
- Other
- mempalace
- MIT
Last pushed
- Memori
- Aug 18, 2026
- mempalace
- Sep 18, 2026
Categories
- Memori
- AI Agents, Data & Retrieval
- mempalace
- Data & Retrieval, Vector Databases
Trust and health
Open issues (now)
- Memori
- 33
- mempalace
- 735
Stars delta
- Memori
- +515 (30d)
- mempalace
- +743 (30d)
Open issues delta
- Memori
- +7 (30d)
- mempalace
- +31 (30d)
Full report
- Memori
- Trust report
- mempalace
- Trust report
Typed relationship
Memori alternative mempalaceMemPalace 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: Python runtime · mempalace: Python runtime
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, rag.
- Also covers AI Agents.
- 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 NOT to use Memori
- （TypeScriptPython），MemoriSDK。
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, embedding, mcp.
- Also covers Vector Databases.
- 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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (MemoriLabs/Memori) · observed Sep 20, 2026
- GitHub forks (MemoriLabs/Memori) · observed Sep 20, 2026
- Last push (MemoriLabs/Memori) · observed Aug 18, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (MemPalace/mempalace) · observed Sep 20, 2026
- GitHub forks (MemPalace/mempalace) · observed Sep 20, 2026
- Last push (MemPalace/mempalace) · observed Sep 18, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Oct 4, 2026
GitHub stars on cards: Memori 16k · mempalace 59k (synced Sep 20, 2026).
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, rag; Also covers AI Agents; 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, embedding, mcp; Also covers Vector Databases; 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 Memori?
- （TypeScriptPython），MemoriSDK。
- 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 Memori or mempalace more popular on GitHub?
- mempalace has more GitHub stars (59,143 vs 16,130). 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 and mempalace alternatives (Memori markdown twin, mempalace markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, Memori or mempalace?
- Memori: Very 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; mempalace trust report.