[langgraph]: Aerospike integration for LangGraph Checkpoint and Store

[havvari-V0]

Type of issue

request for content

Language

Python

Description

Integration Overview

We’ve built Aerospike-backed persistence integrations for LangGraph, published as standalone Python packages:

• Checkpointing: langgraph-checkpoint-aerospike
  PyPI: https://pypi.org/project/langgraph-checkpoint-aerospike/
  GitHub: https://github.com/aerospike/aerospike-langgraph/tree/main/packages/langgraph-checkpoint-aerospike
• Store: langgraph-store-aerospike
  PyPI: https://pypi.org/project/langgraph-store-aerospike/
  GitHub: https://github.com/aerospike/aerospike-langgraph/tree/main/packages/langgraph-store-aerospike

These integrations allow LangGraph users to persist graph state, checkpoints, and stored data in Aerospike, enabling durable, resumable, and scalable agent workflows.

LangGraph Surfaces Supported

• Checkpointer (AerospikeSaver)
• Store (AerospikeStore)

Why This Matters

Aerospike provides high-performance, low-latency persistence with TTL support and is commonly used in production systems that require durability and scale. These integrations enable LangGraph users to run long-lived and stateful agents with reliable backend storage.

Call To Action (CTA)

Could you advise on the appropriate location in the LangChain / LangGraph documentation to represent these integrations (e.g., existing memory page vs. a dedicated checkpointer/store integrations page)?
Once the correct placement is confirmed, we’re happy to submit a documentation PR.