LangGraph Persistence
https://docs.langchain.com/oss/python/langgraph/persistence
Distinct from LangMem. Built-in checkpointer saves graph state per super-step (short-term, thread-scoped). Store System adds long-term hierarchical key-value memory across threads with optional vector search + TTL. Postgres / Mongo / Redis stores for production.
At a glance
- Type
- Checkpoints + Store System
- Tier
- T2
- Section
- Framework-embedded memory
- Created
- 2024-01 (LangGraph v0.1 released Jan 2024; long-term memory persistence added Oct 2024)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- OSS free (MIT); LangGraph Platform (now LangSmith Deployment as of Oct 2025): Free Developer plan 100k nodes/mo; Pl…
- Funding
- $160M total (LangChain parent); $1.2B valuation; Series B Oct 2025
Taxonomy
- storage
- relational
- retrieval
- exact-match
- persistence
- cross-session
- update
- overwrite
- unit
- episode
- governance
- inspectable
- conflict
- last-write-wins
When to use
Optimised for: durable graph-state checkpointing + Store System for cross-thread memory
Anti-fit: not for non-LangGraph workflows
Pros & cons
Pros
Persistent state for graph agents — checkpointing and resumability are first-class, not bolted on.
Cons
LangGraph-shaped; persistence model is general but most idiomatic when paired with LangChain memory.
Claims & capabilities
Checkpointer saves graph state at every superstep enabling memory between interactions, human-in-the-loop, and fault tolerance. Multiple backends: MemorySaver (in-memory), PostgresSaver, AsyncPostgresSaver, langgraph-checkpoint-redis (Redis integration). Part of LangChain ecosystem ($160M Series B, $1.2B valuation, October 2025)
Technical surface
- API surface
- SDK: Python, JS/TS
- Backend storage
- pluggable (Postgres, SQLite, Redis)
- Deployment
- Both (LangGraph OSS self-hosted; LangSmith Deployment cloud managed or self-hosted)
- Embedding model
- multiple supported
- Multi-tenancy
- not applicable — library; namespace is (thread_id, checkpoint_ns); hosted LangGraph Cloud runs in Anthropic-managed VPC
- MCP
- via official adapter — LangChain MCP adapters
- A2A
- supported — LangGraph A2A wrappers
- OpenTelemetry
- first-class — LangSmith + OTel
Compare LangGraph Persistence with…
Similar systems
Other framework-embedded memory in the catalog, ranked by inbound references.
- AutoGen Memory T2
ListMemory chronological context + teachable agents that vectorise corrections. Integrates with Mem0/Zep rather than building deep memory natively.
- CrewAI Memory T2
Memory subsystem inside the CrewAI orchestration framework; integrates with Mem0 for the long-term tier.
- AGiXT Adaptive Memory T2
Open-source AI automation platform. Routes between short-term and long-term memory adaptively across any LLM provider; plugin system for storage backends. Memory managed at the instruction-management layer — task context, instruction state, conversation history as unified agent state.
- Agno (Phidata) Memory T2
Agno (formerly Phidata). AgentStorage persists sessions to a DB; AgentMemory auto-classifies/store user preferences and conversation summaries. Single-line integrations with LanceDB, Pinecone, Weaviate, Qdrant.
- Botpress LLMz T1
Per-plan vector-DB storage quota + LLMz autonomous engine (in-session working memory) + Knowledge Base (semantic search over uploaded docs). Long-term user memory persists across sessions.
- DSPy History T3
dspy.History primitive — typed field holding messages: list[dict] that slots into any Signature . No persistent memory of its own; purely a structured context-injection contract. DSPy's optimisation loop (MIPRO, BootstrapFewShot) treats historical turns as trainable few-shot structure.
Related systems
References (2)
- LangGraph (orchestration) depends on at runtime — adjacent-infrastructure cell: requires LangGraph; checkpointer (SQLite/Postgres)
- MongoDB Atlas Vector Search builds on — Postgres / Mongo / Redis stores for production.
Referenced by (6)
- AWS Bedrock AgentCore Memory integrates with — Native integrations with LangChain/LangGraph and Strands.
- Burr (DAGWorks) competes with — itions; lightweight alternative to LangGraph.
- LangMem (LangChain) integrates with — First-party LangChain integration so memory composes with retrievers, chains, and graphs without glue code.
- LangSmith integrates with — de-facto trace tool for that ecosystem
- mcp-memory-service (doobidoo) integrates with — Agent-pipeline focused (LangGraph, CrewAI, AutoGen)
- MongoDB Atlas Vector Search integrates with — LangGraph checkpointer for stateful agents.