Comparison
mempalace vs memsearch
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 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.
Markdown twin · mempalace alternatives · memsearch alternatives
GraphCanon updated Oct 4, 2026
17views this month
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Trust & integrity
| Signal | mempalace | memsearch |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Oct 4, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- mempalace
- The best-benchmarked open-source AI memory system
- memsearch
- A persistent, unified memory layer for all your AI agents backed by Markdown and Milvus.
Stars
- mempalace
- 59k
- memsearch
- 2.6k
Forks
- mempalace
- 7.6k
- memsearch
- 253
Open issues
- mempalace
- 735
- memsearch
- 254
Language
- mempalace
- Python
- memsearch
- Python
Adopt for
- 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.
- memsearch
- 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
- mempalace
- -
- memsearch
- -
Runtime
- mempalace
- -
- memsearch
- -
License
- mempalace
- MIT
- memsearch
- MIT
Last pushed
- mempalace
- Sep 18, 2026
- memsearch
- Sep 20, 2026
Categories
- mempalace
- Data & Retrieval, Vector Databases
- memsearch
- AI Agents, Data & Retrieval, Vector Databases
Trust and health
Open issues (now)
- mempalace
- 735
- memsearch
- 254
Stars delta
- mempalace
- +743 (30d)
- memsearch
- +291 (30d)
Open issues delta
- mempalace
- +31 (30d)
- memsearch
- +23 (30d)
Full report
- mempalace
- Trust report
- memsearch
- Trust report
Typed relationship
mempalace alternative memsearchBoth MemPalace and memsearch offer persistent memory layers for AI agents but utilize different storage backends (ChromaDB vs Markdown + Milvus).
Choose mempalace if…
- Both MemPalace and memsearch offer persistent memory layers for AI agents but utilize different storage backends (ChromaDB vs Markdown + Milvus).
- 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 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.
Choose memsearch if…
- Both MemPalace and memsearch offer persistent memory layers for AI agents but utilize different storage backends (ChromaDB vs Markdown + Milvus).
- Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search.
- Also covers AI Agents.
- When you need robust integration with AI agents like Claude Code or Codex
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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (zilliztech/memsearch) · observed Sep 20, 2026
- GitHub forks (zilliztech/memsearch) · observed Sep 20, 2026
- Last push (zilliztech/memsearch) · observed Sep 20, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: mempalace 59k · memsearch 2.6k (synced Sep 20, 2026).
Common questions
- What is the difference between mempalace and memsearch?
- mempalace: The best-benchmarked open-source AI memory system. 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 mempalace over memsearch?
- Choose mempalace over memsearch when Both MemPalace and memsearch offer persistent memory layers for AI agents but utilize different storage backends (ChromaDB vs Markdown + Milvus); 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 choose memsearch over mempalace?
- Choose memsearch over mempalace when Both MemPalace and memsearch offer persistent memory layers for AI agents but utilize different storage backends (ChromaDB vs Markdown + Milvus); Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search; Also covers AI Agents; When you need robust integration with AI agents like Claude Code or Codex.
- 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 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 mempalace or memsearch more popular on GitHub?
- mempalace has more GitHub stars (59,143 vs 2,627). Stars measure visibility, not whether either tool fits your constraints.
- Are mempalace and memsearch open source?
- Yes - both are open-source projects on GitHub (mempalace: MIT, memsearch: MIT).
- Where can I find alternatives to mempalace or memsearch?
- GraphCanon lists graph-backed alternatives at mempalace alternatives and memsearch alternatives (mempalace markdown twin, memsearch 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, mempalace or memsearch?
- mempalace: Very 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 mempalace and memsearch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mempalace trust report; memsearch trust report.