--- title: "graphiti vs langgraph" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/getzep-graphiti-vs-langchain-ai-langgraph" tools: ["getzep-graphiti", "langchain-ai-langgraph"] --- # graphiti vs langgraph *GraphCanon updated Aug 18, 2026* ## 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 langgraph if langGraph is designed as an open-source orchestration framework to build stateful AI agents. It emphasizes durable execution and human-in-the-loop interventions, along with. [graphiti](https://help.getzep.com/graphiti) reports 30k GitHub stars, 3.0k forks, and 488 open issues, last pushed Aug 17, 2026. [langgraph](https://docs.langchain.com/oss/python/langgraph/) has 38k stars, 6.5k forks, and 647 open issues, last pushed Jul 28, 2026. Figures are from public GitHub metadata via [graphiti's repository](https://github.com/getzep/graphiti) and [langgraph's repository](https://github.com/langchain-ai/langgraph). | | [graphiti](/tools/getzep-graphiti.md) | [langgraph](/tools/langchain-ai-langgraph.md) | | --- | --- | --- | | Tagline | Build Real-Time Knowledge Graphs for AI Agents | Low-level orchestration framework for building stateful agents. | | Stars | 30,018 | 38,352 | | Forks | 3,042 | 6,458 | | Open issues | 488 | 647 | | Language | Python | Python | | Adopt for | 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 | LangGraph is designed as an open-source orchestration framework to build stateful AI agents. It emphasizes durable execution and human-in-the-loop interventions, along with robust memory management capabilities. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, LLM Frameworks | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [graphiti](/tools/getzep-graphiti.md) | [langgraph](/tools/langchain-ai-langgraph.md) | | --- | --- | --- | | Open issues (now) | 488 | 647 | | Stars delta | +1.1k (30d) | Unknown | | Open issues delta | +45 (30d) | Unknown | | Full report | [trust report](/tools/getzep-graphiti/trust.md) | [trust report](/tools/langchain-ai-langgraph/trust.md) | ## Shared compatibility - **Python**: [graphiti](/tools/getzep-graphiti.md) - Python runtime; [langgraph](/tools/langchain-ai-langgraph.md) - Python runtime ## Decision facts: graphiti - **Adopt for:** 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 ## Decision facts: langgraph - **Pricing:** freemium - LangGraph is available under the MIT license and is free for both personal and commercial use. However, advanced features or services like deployment and debugging might depend on additional paid-for- - **Requirements:** Min 4 GB RAM; Requires Python environment - **Adopt for:** LangGraph is designed as an open-source orchestration framework to build stateful AI agents. It emphasizes durable execution and human-in-the-loop interventions, along with robust memory management capabilities. ## Choose when ### Choose graphiti if… - License: graphiti is Apache-2.0, langgraph is MIT. - 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. ### Choose langgraph if… - License: langgraph is MIT, graphiti is Apache-2.0. - Pricing: LangGraph is available under the MIT license and is free for both personal and commercial use. However, advanced features or services like deployment and debugging might depend on additional paid-for-. - Requirements: Min 4 GB RAM; Requires Python environment. - Tags unique to langgraph: ai-agents, enterprise, framework, langchain. - Also covers Developer Tools. - When you need a low-level framework that supports the development of long-running, stateful AI agents that require complex memory management. ## 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. ## When NOT to use langgraph - LangGraph is less suitable when you prefer a simpler setup. It demands more initial configuration and lower-level control than other agent-building frameworks such as Deep Agents. - For projects requiring immediate quick-start capabilities, as LangGraph offers foundational support which involves more manual configuration versus quicker-to-prototype tools. ## Common questions ### What is the difference between graphiti and langgraph? graphiti: Build Real-Time Knowledge Graphs for AI Agents. langgraph: Low-level orchestration framework for building stateful agents.. See the comparison table for live GitHub stats and shared categories. ### When should I choose graphiti over langgraph? Choose graphiti over langgraph when License: graphiti is Apache-2.0, langgraph is MIT; 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 langgraph over graphiti? Choose langgraph over graphiti when License: langgraph is MIT, graphiti is Apache-2.0; Pricing: LangGraph is available under the MIT license and is free for both personal and commercial use. However, advanced features or services like deployment and debugging might depend on additional paid-for-; Requirements: Min 4 GB RAM; Requires Python environment; Tags unique to langgraph: ai-agents, enterprise, framework, langchain; Also covers Developer Tools; When you need a low-level framework that supports the development of long-running, stateful AI agents that require complex memory management. ### 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 langgraph? LangGraph is less suitable when you prefer a simpler setup. It demands more initial configuration and lower-level control than other agent-building frameworks such as Deep Agents. For projects requiring immediate quick-start capabilities, as LangGraph offers foundational support which involves more manual configuration versus quicker-to-prototype tools. ### Is graphiti or langgraph more popular on GitHub? langgraph has more GitHub stars (38,352 vs 30,018). Stars measure visibility, not whether either tool fits your constraints. ### Are graphiti and langgraph open source? Yes - both are open-source projects on GitHub (graphiti: Apache-2.0, langgraph: MIT). ### Where can I find alternatives to graphiti or langgraph? GraphCanon lists graph-backed alternatives at [graphiti alternatives](/tools/getzep-graphiti/alternatives) and [langgraph alternatives](/tools/langchain-ai-langgraph/alternatives) ([graphiti markdown twin](/tools/getzep-graphiti/alternatives.md), [langgraph markdown twin](/tools/langchain-ai-langgraph/alternatives.md)), 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](/compare/getzep-graphiti-vs-langchain-ai-langgraph.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, graphiti or langgraph? graphiti: Very active. langgraph: 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 langgraph? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [graphiti trust report](/tools/getzep-graphiti/trust); [langgraph trust report](/tools/langchain-ai-langgraph/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=getzep-graphiti`](/api/graphcanon/graph?tool=getzep-graphiti) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_