Comparison
OpenMemory vs embedbase
Verdict
Pick OpenMemory if openMemory offers local storage tailored for AI agents like Claude Desktop and GitHub Copilot; pick embedbase if embedbase is a TypeScript-based API designed to facilitate the creation of Large Language Model (LLM) powered applications via integrations with embeddings and vector databases.
Markdown twin · OpenMemory alternatives · embedbase alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | OpenMemory | embedbase |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Dormant (601d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of 4w · 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
- OpenMemory
- Local persistent memory store for LLM applications
- embedbase
- A dead-simple API to build LLM-powered apps
Stars
- OpenMemory
- 4.5k
- embedbase
- 524
Forks
- OpenMemory
- 501
- embedbase
- 55
Open issues
- OpenMemory
- 18
- embedbase
- 35
Language
- OpenMemory
- TypeScript
- embedbase
- TypeScript
Adopt for
- OpenMemory
- OpenMemory offers local storage tailored for AI agents like Claude Desktop and GitHub Copilot.
- embedbase
- Embedbase is a TypeScript-based API designed to facilitate the creation of Large Language Model (LLM) powered applications via integrations with embeddings and vector databases.
Persona
- OpenMemory
- -
- embedbase
- -
Runtime
- OpenMemory
- -
- embedbase
- -
License
- OpenMemory
- Apache-2.0
- embedbase
- MIT
Last pushed
- OpenMemory
- Aug 20, 2026
- embedbase
- Nov 27, 2024
Categories
- OpenMemory
- Data & Retrieval, Vector Databases
- embedbase
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- OpenMemory
- Very active (96%)
- embedbase
- Dormant (18%)
Days since push
- OpenMemory
- 0d
- embedbase
- 601d
Open issues (now)
- OpenMemory
- 18
- embedbase
- 35
Stars delta
- OpenMemory
- +100 (30d)
- embedbase
- Unknown
Open issues delta
- OpenMemory
- +5 (30d)
- embedbase
- Unknown
Full report
- OpenMemory
- Trust report
- embedbase
- Trust report
Choose OpenMemory if…
- License: OpenMemory is Apache-2.0, embedbase is MIT.
- Tags unique to OpenMemory: ai-agents, long-term-memory, memory-engine.
- OpenMemory ships Docker support for self-hosted deployment.
- Need to integrate persistent memory support for specific LLMs like Claude.
When NOT to use OpenMemory
- Require cloud-based memory storage services.
- Your project must use languages other than TypeScript.
- Seek a generic vector database without specific LLM integrations.
Choose embedbase if…
- License: embedbase is MIT, OpenMemory is Apache-2.0.
- Tags unique to embedbase: ai, artificial-intelligence, chatgpt, machine-learning.
- * Use Embedbase if you require direct integration capabilities specifically designed for embeddings and vector databases, like pgvector or Supabase.
When NOT to use embedbase
- * Avoid using Embedbase if your application's technology stack cannot effectively integrate TypeScript, as its primary language support is in this framework and not others like Python.
- * Do not use it when you need extensive customization options for the vector database configurations beyond what pgvector or Supabase offers.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (CaviraOSS/OpenMemory) · observed Aug 21, 2026
- GitHub forks (CaviraOSS/OpenMemory) · observed Aug 21, 2026
- Last push (CaviraOSS/OpenMemory) · observed Aug 20, 2026
- License file (Apache-2.0) · observed Aug 21, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (different-ai/embedbase) · observed Jul 22, 2026
- GitHub forks (different-ai/embedbase) · observed Jul 22, 2026
- Last push (different-ai/embedbase) · observed Nov 27, 2024
- License file (MIT) · observed Jul 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: OpenMemory 4.5k · embedbase 524 (synced Aug 21, 2026).
Common questions
- What is the difference between OpenMemory and embedbase?
- OpenMemory: Local persistent memory store for LLM applications. embedbase: A dead-simple API to build LLM-powered apps. See the comparison table for live GitHub stats and shared categories.
- When should I choose OpenMemory over embedbase?
- Choose OpenMemory over embedbase when License: OpenMemory is Apache-2.0, embedbase is MIT; Tags unique to OpenMemory: ai-agents, long-term-memory, memory-engine; OpenMemory ships Docker support for self-hosted deployment; Need to integrate persistent memory support for specific LLMs like Claude.
- When should I choose embedbase over OpenMemory?
- Choose embedbase over OpenMemory when License: embedbase is MIT, OpenMemory is Apache-2.0; Tags unique to embedbase: ai, artificial-intelligence, chatgpt, machine-learning; * Use Embedbase if you require direct integration capabilities specifically designed for embeddings and vector databases, like pgvector or Supabase.
- When should I avoid OpenMemory?
- Require cloud-based memory storage services. Your project must use languages other than TypeScript. Seek a generic vector database without specific LLM integrations.
- When should I avoid embedbase?
- * Avoid using Embedbase if your application's technology stack cannot effectively integrate TypeScript, as its primary language support is in this framework and not others like Python. * Do not use it when you need extensive customization options for the vector database configurations beyond what pgvector or Supabase offers.
- Is OpenMemory or embedbase more popular on GitHub?
- OpenMemory has more GitHub stars (4,457 vs 524). Stars measure visibility, not whether either tool fits your constraints.
- Are OpenMemory and embedbase open source?
- Yes - both are open-source projects on GitHub (OpenMemory: Apache-2.0, embedbase: MIT).
- Where can I find alternatives to OpenMemory or embedbase?
- GraphCanon lists graph-backed alternatives at OpenMemory alternatives and embedbase alternatives (OpenMemory markdown twin, embedbase 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, OpenMemory or embedbase?
- OpenMemory: Very active. embedbase: Dormant. 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 OpenMemory and embedbase?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: OpenMemory trust report; embedbase trust report.