Comparison
mempalace vs honcho
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 honcho if memory Library for Stateful Agents.
Markdown twin · mempalace alternatives · honcho alternatives
GraphCanon updated Oct 4, 2026
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Trust & integrity
| Signal | mempalace | honcho |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Aug 18, 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 Aug 18, 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
- honcho
- Memory library for building stateful agents
Stars
- mempalace
- 59k
- honcho
- 6.7k
Forks
- mempalace
- 7.6k
- honcho
- 824
Open issues
- mempalace
- 735
- honcho
- 163
Language
- mempalace
- Python
- honcho
- 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.
- honcho
- Memory Library for Stateful Agents
Persona
- mempalace
- -
- honcho
- -
Runtime
- mempalace
- -
- honcho
- -
License
- mempalace
- MIT
- honcho
- AGPL-3.0
Last pushed
- mempalace
- Sep 18, 2026
- honcho
- Aug 18, 2026
Categories
- mempalace
- Data & Retrieval, Vector Databases
- honcho
- AI Agents, Data & Retrieval
Trust and health
Open issues (now)
- mempalace
- 735
- honcho
- 163
Stars delta
- mempalace
- +743 (30d)
- honcho
- +659 (30d)
Open issues delta
- mempalace
- +31 (30d)
- honcho
- -3 (30d)
Full report
- mempalace
- Trust report
- honcho
- Trust report
Typed relationship
mempalace alternative honchoHoncho and mempalace/mempalace both offer memory solutions for AI agents tailored toward benchmarking and improving agent performance over time, making them alternatives in the market.
Shared compatibility
- Python · mempalace: Python runtime · honcho: Python runtime
Choose mempalace if…
- License: mempalace is MIT, honcho is AGPL-3.0.
- Honcho and mempalace/mempalace both offer memory solutions for AI agents tailored toward benchmarking and improving agent performance over time, making them alternatives in the market.
- Tags unique to mempalace: ai, chromadb, embedding, llm.
- 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.
Choose honcho if…
- License: honcho is AGPL-3.0, mempalace is MIT.
- Honcho and mempalace/mempalace both offer memory solutions for AI agents tailored toward benchmarking and improving agent performance over time, making them alternatives in the market.
- Tags unique to honcho: agent-memory, ai-agents, embeddings, langchain.
- Also covers AI Agents.
- Requires managing long-term and contextual memory in AI agents for statefulness.
When NOT to use honcho
- Do not need complex SDK support or a customizable framework approach.
- Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI.
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 (plastic-labs/honcho) · observed Sep 20, 2026
- GitHub forks (plastic-labs/honcho) · observed Sep 20, 2026
- Last push (plastic-labs/honcho) · observed Aug 18, 2026
- License file (AGPL-3.0) · 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 · honcho 6.7k (synced Sep 20, 2026).
Common questions
- What is the difference between mempalace and honcho?
- mempalace: The best-benchmarked open-source AI memory system. honcho: Memory library for building stateful agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose mempalace over honcho?
- Choose mempalace over honcho when License: mempalace is MIT, honcho is AGPL-3.0; Honcho and mempalace/mempalace both offer memory solutions for AI agents tailored toward benchmarking and improving agent performance over time, making them alternatives in the market; Tags unique to mempalace: ai, chromadb, embedding, llm; 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 choose honcho over mempalace?
- Choose honcho over mempalace when License: honcho is AGPL-3.0, mempalace is MIT; Honcho and mempalace/mempalace both offer memory solutions for AI agents tailored toward benchmarking and improving agent performance over time, making them alternatives in the market; Tags unique to honcho: agent-memory, ai-agents, embeddings, langchain; Also covers AI Agents; Requires managing long-term and contextual memory in AI agents for statefulness.
- 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 honcho?
- Do not need complex SDK support or a customizable framework approach. Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI.
- Is mempalace or honcho more popular on GitHub?
- mempalace has more GitHub stars (59,143 vs 6,703). Stars measure visibility, not whether either tool fits your constraints.
- Are mempalace and honcho open source?
- Yes - both are open-source projects on GitHub (mempalace: MIT, honcho: AGPL-3.0).
- Where can I find alternatives to mempalace or honcho?
- GraphCanon lists graph-backed alternatives at mempalace alternatives and honcho alternatives (mempalace markdown twin, honcho 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 honcho?
- mempalace: Very active. honcho: 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 honcho?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mempalace trust report; honcho trust report.