Comparison
mem0 vs Memori
Verdict
Pick mem0 if mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments; 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.
Markdown twin · mem0 alternatives · Memori alternatives
GraphCanon updated Sep 20, 2026
19views this month
Trust & integrity
| Signal | mem0 | Memori |
|---|---|---|
| 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 Sep 18, 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
- mem0
- Drop-in memory infrastructure for AI agents and apps
- Memori
- Agent-native memory infrastructure for LLM systems
Stars
- mem0
- 66k
- Memori
- 16k
Forks
- mem0
- 7.7k
- Memori
- 3.2k
Open issues
- mem0
- 754
- Memori
- 33
Language
- mem0
- Python
- Memori
- Python
Adopt for
- mem0
- mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments.
- 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
Persona
- mem0
- -
- Memori
- -
Runtime
- mem0
- -
- Memori
- -
License
- mem0
- mem0 is distributed under the Apache-2.0 license, allowing for broad usage and modification with attribution.
- Memori
- Other
Last pushed
- mem0
- Sep 18, 2026
- Memori
- Aug 18, 2026
Categories
- mem0
- AI Agents, Data & Retrieval
- Memori
- AI Agents, Data & Retrieval
Trust and health
Open issues (now)
- mem0
- 754
- Memori
- 33
Stars delta
- mem0
- +2.8k (30d)
- Memori
- +515 (30d)
Open issues delta
- mem0
- +63 (30d)
- Memori
- +7 (30d)
Full report
- mem0
- Trust report
- Memori
- Trust report
Typed relationship
mem0 alternative MemoriMemori and mem0 both address the need for agent-native memory infrastructure in LLM systems, presenting them as alternatives with similar goals.
Shared compatibility
- Node.js · mem0: Node.js runtime · Memori: Node.js runtime
- Python · mem0: Python runtime · Memori: Python runtime
Choose mem0 if…
- License: mem0 is Apache-2.0, Memori is Other.
- Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost..
- Requirements: Min 2 GB RAM; Python environment is required for installation and use..
- Memori and mem0 both address the need for agent-native memory infrastructure in LLM systems, presenting them as alternatives with similar goals.
- Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory.
- When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
When NOT to use mem0
- If your project is not in Python, as mem0 is specifically designed for Python environments.
- When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers.
- If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
Choose Memori if…
- License: Memori is Other, mem0 is Apache-2.0.
- Memori and mem0 both address the need for agent-native memory infrastructure in LLM systems, presenting them as alternatives with similar goals.
- Tags unique to Memori: agent-memory, enterprise, llm, typescript.
- Memori ships Docker support for self-hosted deployment.
- 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。
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (mem0ai/mem0) · observed Sep 20, 2026
- GitHub forks (mem0ai/mem0) · observed Sep 20, 2026
- Last push (mem0ai/mem0) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- 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 on cards: mem0 66k · Memori 16k (synced Sep 20, 2026).
Common questions
- What is the difference between mem0 and Memori?
- mem0: Drop-in memory infrastructure for AI agents and apps. Memori: Agent-native memory infrastructure for LLM systems. See the comparison table for live GitHub stats and shared categories.
- When should I choose mem0 over Memori?
- Choose mem0 over Memori when License: mem0 is Apache-2.0, Memori is Other; Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost.; Requirements: Min 2 GB RAM; Python environment is required for installation and use.; Memori and mem0 both address the need for agent-native memory infrastructure in LLM systems, presenting them as alternatives with similar goals; Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory; When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
- When should I choose Memori over mem0?
- Choose Memori over mem0 when License: Memori is Other, mem0 is Apache-2.0; Memori and mem0 both address the need for agent-native memory infrastructure in LLM systems, presenting them as alternatives with similar goals; Tags unique to Memori: agent-memory, enterprise, llm, typescript; Memori ships Docker support for self-hosted deployment; 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 avoid mem0?
- If your project is not in Python, as mem0 is specifically designed for Python environments. When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers. If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
- When should I avoid Memori?
- （TypeScriptPython），MemoriSDK。
- Is mem0 or Memori more popular on GitHub?
- mem0 has more GitHub stars (65,557 vs 16,130). Stars measure visibility, not whether either tool fits your constraints.
- Are mem0 and Memori open source?
- Yes - both are open-source projects on GitHub (mem0: Apache-2.0, Memori: Other).
- Where can I find alternatives to mem0 or Memori?
- GraphCanon lists graph-backed alternatives at mem0 alternatives and Memori alternatives (mem0 markdown twin, Memori 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, mem0 or Memori?
- mem0: Very active. Memori: 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 mem0 and Memori?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mem0 trust report; Memori trust report.