Comparison
graphiti vs mem0
Verdict
Pick graphiti if graphiti is a Python-based toolkit for building real-time knowledge graphs utilized by AI agents, supporting Neo4j, FalkorDB, Amazon Neptune, and Kuzu as database options along with OpenAI, Anthropic, Groq, and Gemini LМ; pick mem0 if mem0 provides a universal memory layer that focuses on long-term memory and state management specifically for AI Agents.
Markdown twin · graphiti alternatives · mem0 alternatives
GraphCanon updated 4d
Trust & integrity
| Signal | graphiti | mem0 |
|---|---|---|
| Maintenance | Very active (0d since push) As of 4d · github_public_v1 | Very active (0d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Organization account As of 2w · 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
- graphiti
- Build Real-Time Knowledge Graphs for AI Agents
- mem0
- Universal memory layer for AI Agents
Stars
- graphiti
- 30k
- mem0
- 63k
Forks
- graphiti
- 3.0k
- mem0
- 7.3k
Open issues
- graphiti
- 488
- mem0
- 691
Language
- graphiti
- Python
- mem0
- Python
Adopt for
- graphiti
- Graphiti is a Python-based toolkit for building real-time knowledge graphs utilized by AI agents, supporting Neo4j, FalkorDB, Amazon Neptune, and Kuzu as database options along with OpenAI, Anthropic, Groq, and Gemini LМ
- mem0
- Mem0 provides a universal memory layer that focuses on long-term memory and state management specifically for AI Agents.
Persona
- graphiti
- -
- mem0
- -
Runtime
- graphiti
- -
- mem0
- -
License
- graphiti
- Apache-2.0
- mem0
- Apache-2.0
Last pushed
- graphiti
- Aug 17, 2026
- mem0
- Aug 7, 2026
Categories
- graphiti
- AI Agents, LLM Frameworks
- mem0
- AI Agents
Trust and health
Open issues (now)
- graphiti
- 488
- mem0
- 691
Stars delta
- graphiti
- +1.1k (30d)
- mem0
- +2.4k (30d)
Open issues delta
- graphiti
- +45 (30d)
- mem0
- +187 (30d)
Full report
- graphiti
- Trust report
- mem0
- Trust report
Typed relationship
graphiti alternative mem0Mem0 is another universal memory layer for AI Agents, which competes with Graphiti's temporal context graphs in managing agent memory and context.
Shared compatibility
- Python · graphiti: Python runtime · mem0: Python runtime
Choose graphiti if…
- Mem0 is another universal memory layer for AI Agents, which competes with Graphiti's temporal context graphs in managing agent memory and context.
- Tags unique to graphiti: amazon-neptune, falkordb, graph, llms.
- Also covers LLM Frameworks.
- graphiti ships Docker support for self-hosted deployment.
- If you require seamless integration with LLM services that support structured output like OpenAI, Anthropic, or Google Gemini.
When NOT to use graphiti
- Consider alternative tools if your project primarily uses non-compliant LLM providers without structured output support.
- If you prefer not to use Python or do not need the capability to build real-time knowledge graphs for AI applications.
Choose mem0 if…
- Pricing: Mem0 is available under the Apache-2.0 license which is free to use. However, additional enterprise support or premium features may have associated costs..
- Requirements: Min 4 GB RAM.
- Mem0 is another universal memory layer for AI Agents, which competes with Graphiti's temporal context graphs in managing agent memory and context.
- Tags unique to mem0: ai, chatbots, llm, long-term-memory.
- - You are working on an AI agent or chatbot application where maintaining a long-term memory is crucial.
When NOT to use mem0
- - If your application does not require the retention of historical context for effective performance over multiple sessions.
- - When you are looking for a general-purpose library or framework that offers features beyond memory management and state handling, such as natural language processing or machine learning models.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (getzep/graphiti) · observed Aug 18, 2026
- GitHub forks (getzep/graphiti) · observed Aug 18, 2026
- Last push (getzep/graphiti) · observed Aug 17, 2026
- License file (Apache-2.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (mem0ai/mem0) · observed Aug 7, 2026
- GitHub forks (mem0ai/mem0) · observed Aug 7, 2026
- Last push (mem0ai/mem0) · observed Aug 7, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: graphiti 30k · mem0 63k (synced Aug 18, 2026).
Common questions
- What is the difference between graphiti and mem0?
- graphiti: Build Real-Time Knowledge Graphs for AI Agents. mem0: Universal memory layer for AI Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose graphiti over mem0?
- Choose graphiti over mem0 when Mem0 is another universal memory layer for AI Agents, which competes with Graphiti's temporal context graphs in managing agent memory and context; Tags unique to graphiti: amazon-neptune, falkordb, graph, llms; Also covers LLM Frameworks; graphiti ships Docker support for self-hosted deployment; If you require seamless integration with LLM services that support structured output like OpenAI, Anthropic, or Google Gemini.
- When should I choose mem0 over graphiti?
- Choose mem0 over graphiti when Pricing: Mem0 is available under the Apache-2.0 license which is free to use. However, additional enterprise support or premium features may have associated costs.; Requirements: Min 4 GB RAM; Mem0 is another universal memory layer for AI Agents, which competes with Graphiti's temporal context graphs in managing agent memory and context; Tags unique to mem0: ai, chatbots, llm, long-term-memory; - You are working on an AI agent or chatbot application where maintaining a long-term memory is crucial.
- When should I avoid graphiti?
- Consider alternative tools if your project primarily uses non-compliant LLM providers without structured output support. If you prefer not to use Python or do not need the capability to build real-time knowledge graphs for AI applications.
- When should I avoid mem0?
- - If your application does not require the retention of historical context for effective performance over multiple sessions. - When you are looking for a general-purpose library or framework that offers features beyond memory management and state handling, such as natural language processing or machine learning models.
- Is graphiti or mem0 more popular on GitHub?
- mem0 has more GitHub stars (62,757 vs 30,018). Stars measure visibility, not whether either tool fits your constraints.
- Are graphiti and mem0 open source?
- Yes - both are open-source projects on GitHub (graphiti: Apache-2.0, mem0: Apache-2.0).
- Where can I find alternatives to graphiti or mem0?
- GraphCanon lists graph-backed alternatives at graphiti alternatives and mem0 alternatives (graphiti markdown twin, mem0 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, graphiti or mem0?
- graphiti: Very active. mem0: 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 graphiti and mem0?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: graphiti trust report; mem0 trust report.