“1. LangGraph Best for complex workflows”
“Best for complex workflows”
“Explicit control over state, branching, loops and human approvals.”
“Good for long-running, stateful and multi-agent systems.”
“Workflows live in normal repositories and can be tested and reviewed.”
“2. OpenAI Agents SDK Best for lightweight code-first agents”
“Best for lightweight code-first agents”
“Build agents directly in Python or TypeScript.”
“Includes tracing, sessions and human-in-the-loop capabilities.”
“4. Mastra Best for TypeScript teams”
“Native TypeScript agent and workflow development.”
“Includes memory, RAG, evaluations and observability.”
“Fits naturally into npm-based projects and standard Git workflows.”
“5. CrewAI Best for role-based multi-agent teams”
“Best for role-based multi-agent teams”
“Define agents, roles, tasks and collaboration in Python.”
“Supports event-driven Flows and more structured orchestration.”
“3. PydanticAI Best for Python engineering teams”
“Strong typing and structured outputs.”
“Explicit dependency injection and tool definitions.”
“Code-first testing and evaluation.”
“Particularly attractive for teams building production Python services.”
“Temporal | Durable workflows, retries, state and long-running execution”
“Temporal | Durable workflows, retries, state and long-running execution”
“Enterprise-grade durable execution | Temporal + an agent SDK”
“Prefect | Python workflow orchestration”
“Prefect | Python workflow orchestration”
“Apache Airflow | Scheduled and dependency-driven pipelines”
“Apache Airflow | Scheduled and dependency-driven pipelines”
“Argo Workflows | Kubernetes-native workflow execution”
“Argo Workflows | Kubernetes-native workflow execution”