Flowise vs LangGraph

Detailed side-by-side comparison to help you choose the right tool

Flowise

🟡Low Code

AI app platform

Flowise supports visual flow builder, agent orchestration, api deployment for prototyping assistants and low-code agent workflows.

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Starting Price

Free

LangGraph

🔴Developer

AI agent framework

LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.

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Starting Price

Free

Feature Comparison

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FeatureFlowiseLangGraph
CategoryAI app platformAI agent framework
Pricing Plans22 tiers8 tiers
Starting PriceFreeFree
Key Features
  • • Visual node-based builder for AI agents and chatflows
  • • Agentflow multi-agent orchestration
  • • Chat assistants with RAG and tool calling
  • • Graph-based workflow orchestration
  • • Deterministic state machine execution
  • • Human-in-the-loop workflows

💡 Our Take

Choose Flowise if your team values visual development speed and includes non-engineers who can configure workflows without writing code. Choose LangGraph if you're a senior LangChain developer who needs fine-grained control over agent state machines and cyclic graphs.

Flowise - Pros & Cons

Pros

  • ✓Apache 2.0 self-hosting offers strong control and flexibility
  • ✓Visual editing speeds up prototypes and stakeholder demos
  • ✓Many connectors cover common model and retrieval stacks
  • ✓Each flow can become an API rather than staying a diagram

Cons

  • ✗Complex canvases can become hard to maintain
  • ✗Self-hosters own authentication, upgrades, monitoring, and scaling
  • ✗Breaking changes require version pinning and testing
  • ✗Cloud execution limits can affect chatty or high-volume agents

LangGraph - Pros & Cons

Pros

  • ✓Open-source library is MIT-licensed and runs anywhere without platform lock-in
  • ✓Native checkpointing makes durable, resumable, human-in-the-loop agents straightforward
  • ✓First-class multi-agent patterns: supervisor, hierarchical, sequential, parallel branches
  • ✓Tight integration with LangSmith for production observability, evaluations, and replays
  • ✓Active maintenance from the LangChain team with frequent releases and strong community

Cons

  • ✗More verbose than LangChain for simple agents — explicit state schemas and edge functions add overhead
  • ✗LangSmith trace pricing ($2.50/1k base traces) is a real cost at production scale
  • ✗LCU + deployment-minute billing makes pricing harder to predict than seat-only competitors
  • ✗Steeper learning curve than role-based frameworks like CrewAI for newcomers
  • ✗Best documented in Python; JavaScript SDK exists but lags in features

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🔒 Security & Compliance Comparison

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Security FeatureFlowiseLangGraph
SOC2—✅ Yes
GDPR—✅ Yes
HIPAA——
SSO—✅ Yes
Self-Hosted✅ Yes🔀 Hybrid
On-Prem✅ Yes✅ Yes
RBAC✅ Yes✅ Yes
Audit Log—✅ Yes
Open Source✅ Yes✅ Yes
API Key Auth✅ Yes✅ Yes
Encryption at Rest—✅ Yes
Encryption in Transit✅ Yes✅ Yes
Data Residencyself-hosted deployments allow user-controlled data residency—
Data Retentionconfigurableconfigurable
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