LangGraph vs Zep
Detailed side-by-side comparison to help you choose the right tool
LangGraph
Agent Frameworks
Graph-based stateful orchestration runtime for agent loops.
Starting Price
Custom
Zep
Memory & State
Temporal knowledge graph and memory store for assistants.
Starting Price
Custom
Feature Comparison
| Feature | LangGraph | Zep |
|---|---|---|
| Category | Agent Frameworks | Memory & State |
| Pricing Plans | 19 tiers | 19 tiers |
| Starting Price | ||
| Key Features |
|
|
LangGraph - Pros & Cons
Pros
- ✓State-machine approach provides fine-grained control over agent flows
- ✓Tight integration with the broader LangChain ecosystem
- ✓Built-in persistence for durable, long-running workflows
- ✓Cloud deployment option via LangSmith for production scale
- ✓Supports cyclic graphs enabling iterative agent reasoning
Cons
- ✗Tightly coupled to LangChain — harder to use standalone
- ✗Graph-based paradigm has a learning curve for new developers
- ✗Cloud features require a LangSmith subscription
- ✗Verbose configuration for simple linear workflows
Zep - Pros & Cons
Pros
- ✓Specialized long-term memory for AI assistants and chatbots
- ✓Automatic summarization of conversation history
- ✓Entity extraction for structured knowledge retention
- ✓Open-source with self-hosting option
- ✓Purpose-built for conversational AI memory management
Cons
- ✗Narrowly focused on conversational memory use cases
- ✗Self-hosting requires additional infrastructure
- ✗Cloud service pricing for production workloads
- ✗Integration requires adapting your application's session management