Comparison Preset
LangGraph is the more defensible choice due to its lower security risk profile, showing one MODERATE vulnerability compared to Agno's known CRITICAL vulnerability. For an enterprise architect, avoiding a critical vulnerability is a primary concern when justifying technology choices to stakeholders. Both frameworks demonstrate strong project health with identical bus factor scores (8/10) and commit frequencies, indicating good long-term maintainability. While Agno's features like a control plane and explicit data ownership are compelling, LangGraph's better security posture makes it the more prudent selection. The MIT license is also widely accepted and poses minimal legal risk.
Overview
The bottom line — what this framework is, who it's for, and when to walk away.
Bottom Line Up Front
Agno provides a production-grade runtime for building, deploying, and managing agentic software, from single agents to coordinated teams and workflows. It features a scalable, stateless FastAPI backend, robust state management in your database, and a control plane for monitoring and governance. It emphasizes user ownership of data and infrastructure.
LangGraph is a low-level Python framework for orchestrating stateful, long-running AI agents using a graph-based approach. It focuses on capabilities like durable execution, comprehensive memory, and human-in-the-loop interactions. While it integrates with LangChain components, it provides fine-grained control for complex agent designs.
Best For
Building, deploying, and managing scalable, production-ready agentic software, teams, and workflows.
Building and deploying complex, stateful, long-running agent workflows requiring granular control.
Avoid If
no data
Starting with agents, or requiring a higher-level abstraction than a graph-based runtime.
Strengths
- +Runtime specifically designed for agentic software, teams, and workflows.
- +Includes memory, knowledge, guardrails, and over 100 integrations for agent development.
- +Provides a stateless, horizontally scalable FastAPI backend for production deployment.
- +Offers a control plane (AgentOS UI) for testing, monitoring, and managing systems in production.
- +Supports per-user and per-session isolation with runtime approval enforcement.
- +Features native tracing and full auditability.
- +Stores sessions, memory, knowledge, and traces in the user's database, ensuring data ownership.
- +Runs in the user's infrastructure, not Agno's.
- +Provides durable execution, allowing agents to persist through failures and resume from where they left off.
- +Supports human-in-the-loop workflows, enabling inspection and modification of agent state at any point.
- +Offers comprehensive memory capabilities for both short-term working memory and long-term memory across sessions.
- +Integrates with LangSmith Observability for deep visibility into agent behavior, tracing, and debugging.
- +Designed for production-ready deployment of scalable, stateful, long-running agent systems.
- +Can be used standalone without relying on other LangChain components.
Weaknesses
- −It is a very low-level orchestration framework, requiring developers to understand underlying agent components.
- −It does not abstract prompts or architecture, demanding manual definition of these elements.
- −Not recommended for beginners or those seeking a higher-level abstraction, as LangChain's agents offer prebuilt architectures.
- −Requires familiarity with components like models and tools before effective use.
Project Health
Is this project alive, well-maintained, and safe to bet on long-term?
Bus Factor Score
Maintainers
Open Issues
Fit
Does it support the workflows, patterns, and capabilities your team actually needs?
State Management
State is managed externally in the user's database for sessions, memory, knowledge, and traces, with a stateless, session-scoped FastAPI backend.
LangGraph manages state through its `StateGraph` abstraction, enabling the definition of custom state objects like `MessagesState` for persisting agent progress and memory across executions.
Cost & Licensing
What does it actually cost? License type, pricing model, and hidden fees.
License
Perspective
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