langgraph-checkpoint-aws
A LangChain checkpointer implementation that uses Bedrock Session Management Service and ElastiCache Valkey to enable stateful and resumable LangGraph agents.
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has low install friction, carries a permissive MIT license, and provides well-integrated AWS persistence options for LangGraph agents. Choose it if you are building stateful agents on AWS and need checkpoint storage, document retrieval, or LLM response caching. No security vulnerabilities are known.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later and AWS credentials configured for the target region.
- Low friction install with four runtime dependencies.
- Actively maintained as of 2026-08-14 with recent releases; repository shows 340 stars and no archived status.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; you must include a copy of the license and copyright notice.
last release 2026-08-13 (1 days) · last repo commit 2026-08-14 · 340 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 567,212 downloads/mo, #5,970 on PyPI
Alternatives
Verify before relying
pip install langgraph-checkpoint-aws
from langgraph_checkpoint_aws import AgentCoreMemorySaver
from langgraph.prebuilt import create_react_agent
checkpointer = AgentCoreMemorySaver("YOUR_MEMORY_ID", region_name="us-west-2")
graph = create_react_agent(model=model, tools=tools, checkpointer=checkpointer)
config = {"configurable": {"thread_id": "session-1", "actor_id": "agent-1"}}
response = graph.invoke({"messages": [("human", "your prompt")]}, config=config)- Whether DynamoDB vector search via semantic indexes requires additional setup or AWS service enablement beyond standard DynamoDB.
- Performance characteristics and latency profiles for each storage backend under production load.
- Exact compression algorithm and storage overhead reduction achieved by enable_checkpoint_compression.
- Whether Valkey optional dependency is required for all use cases or only for specific storage backends.
What it is and what it does
LangGraph Checkpoint AWS is a persistence layer for LangGraph agents that integrates with AWS services. It offers three main storage strategies: Bedrock AgentCore Memory for managed session storage, DynamoDB with optional S3 offloading for checkpoint and document storage with vector search, and Valkey (Redis-compatible) for high-performance caching and checkpointing. The package acts as a checkpointer and document store, allowing LangGraph agents to resume from saved state across sessions and to retrieve long-term memories and preferences.
The package is designed for developers building stateful, resumable agents on AWS infrastructure. It handles the integration between LangGraph's checkpoint interface and AWS backend services, including automatic compression, TTL management, and intelligent offloading of large checkpoints to S3. Runtime dependencies are langgraph, langgraph-checkpoint, boto3, and typing_extensions; Valkey support is optional.
Use it for
- Build resumable chatbot agents that persist conversation state across sessions using Bedrock AgentCore Memory.
- Store agent checkpoints in DynamoDB with automatic S3 offloading for long-running or memory-intensive workflows.
- Cache LLM responses and computation results using Valkey to reduce latency and API costs.
- Implement semantic search over agent memories and preferences stored in DynamoDB vector indexes.
- Deploy multi-actor agent systems where each actor maintains separate session state via configurable thread and actor IDs.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has low install friction, carries a permissive MIT license, and provides well-integrated AWS persistence options for LangGraph agents. Choose it if you are building stateful agents on AWS and need checkpoint storage, document retrieval, or LLM response caching. No security vulnerabilities are known.
Install
langgraph-checkpoint-aws on PyPI
Before you install
Low friction install with four runtime dependencies. Actively maintained as of 2026-08-14 with recent releases; repository shows 340 stars and no archived status.
Requires Python 3.10 or later and AWS credentials configured for the target region.
License in practice
MIT license permits commercial and private use with minimal restrictions; you must include a copy of the license and copyright notice.
Quickstart
pip install langgraph-checkpoint-aws
from langgraph_checkpoint_aws import AgentCoreMemorySaver
from langgraph.prebuilt import create_react_agent
checkpointer = AgentCoreMemorySaver("YOUR_MEMORY_ID", region_name="us-west-2")
graph = create_react_agent(model=model, tools=tools, checkpointer=checkpointer)
config = {"configurable": {"thread_id": "session-1", "actor_id": "agent-1"}}
response = graph.invoke({"messages": [("human", "your prompt")]}, config=config)Verify before relying
- Whether DynamoDB vector search via semantic indexes requires additional setup or AWS service enablement beyond standard DynamoDB.
- Performance characteristics and latency profiles for each storage backend under production load.
- Exact compression algorithm and storage overhead reduction achieved by enable_checkpoint_compression.
- Whether Valkey optional dependency is required for all use cases or only for specific storage backends.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packageslanggraph-checkpointlanggraphboto3typing_extensions |
| Maintenance | Actively maintained 1 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 567,212 / month, #5,970 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: langgraph_checkpoint_aws-1.2.2-py3-none-any.whl
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See also langgraph-checkpoint-redis · langgraph-checkpoint · langgraph-checkpoint-postgres · langgraph-checkpoint-mongodb · bedrock-agentcore · langgraph-checkpoint-sqlite · langgraph-runtime-inmem · langmem · langgraph-supervisor · langchain-postgres