Comparison
mempalace vs honcho
Verdict
Pick mempalace if memPalace is an advanced open-source AI memory system that integrates with ChromaDB to optimize machine learning model memories and enhance data retrieval efficiency; pick honcho if memory Library for Stateful Agents.
Markdown twin · mempalace alternatives · honcho alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | mempalace | honcho |
|---|---|---|
| Maintenance | Very active (1d since push) As of 5d · github_public_v1 | Very active (0d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 5d · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- 58k
- honcho
- 6.7k
Forks
- mempalace
- 7.5k
- honcho
- 824
Open issues
- mempalace
- 704
- honcho
- 163
Language
- mempalace
- Python
- honcho
- Python
Adopt for
- mempalace
- MemPalace is an advanced open-source AI memory system that integrates with ChromaDB to optimize machine learning model memories and enhance data retrieval efficiency.
- honcho
- Memory Library for Stateful Agents
Persona
- mempalace
- -
- honcho
- -
Runtime
- mempalace
- -
- honcho
- -
License
- mempalace
- MIT
- honcho
- AGPL-3.0
Last pushed
- mempalace
- Aug 15, 2026
- honcho
- Aug 18, 2026
Categories
- mempalace
- Model Training, Vector Databases
- honcho
- AI Agents, Data & Retrieval
Trust and health
Days since push
- mempalace
- 1d
- honcho
- 0d
Open issues (now)
- mempalace
- 704
- honcho
- 163
Stars delta
- mempalace
- +1.0k (30d)
- honcho
- +659 (30d)
Open issues delta
- mempalace
- +77 (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, llm.
- Also covers Model Training, Vector Databases.
- When you need a highly benchmarked solution for managing AI model memories, MemPalace can provide superior performance due to its optimization features integrated specifically around ML model needs.
When NOT to use mempalace
- Avoid if requiring a proprietary system where full transparency or customization of the memory management layer may not be necessary, since MemPalace is open source and might involve deeper technical
- If your project strictly adheres to non-MIT licenses, then MemPalace might not be suitable due to its MIT license which may conflict with licensing requirements.
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, Data & Retrieval.
- 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 Aug 16, 2026
- GitHub forks (MemPalace/mempalace) · observed Aug 16, 2026
- Last push (MemPalace/mempalace) · observed Aug 15, 2026
- License file (MIT) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (plastic-labs/honcho) · observed Aug 18, 2026
- GitHub forks (plastic-labs/honcho) · observed Aug 18, 2026
- Last push (plastic-labs/honcho) · observed Aug 18, 2026
- License file (AGPL-3.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: mempalace 58k · honcho 6.7k (synced Aug 16, 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, llm; Also covers Model Training, Vector Databases; When you need a highly benchmarked solution for managing AI model memories, MemPalace can provide superior performance due to its optimization features integrated specifically around ML model needs.
- 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, Data & Retrieval; Requires managing long-term and contextual memory in AI agents for statefulness.
- When should I avoid mempalace?
- Avoid if requiring a proprietary system where full transparency or customization of the memory management layer may not be necessary, since MemPalace is open source and might involve deeper technical If your project strictly adheres to non-MIT licenses, then MemPalace might not be suitable due to its MIT license which may conflict with licensing requirements.
- 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 (58,400 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.