We have N8N Self Hosted using queues, we recently upgrades to version 2.4.8. We are heavily using AI related nodes. After the update we notice that SImple Memory node is gone (not showing in the list of Agent Node when you choose Memory. Reading the docs it seems now Simple Memory Node is not supported when using queues. We built a lot on top of it and I would like to know if you are working on a short-term solution to have Simple Memory back or understand alternatives.
What is the error message (if any)?
Normal workflow errors since Simple Memory is not showing anymore
Please share your workflow
(Select the nodes on your canvas and use the keyboard shortcuts CMD+C/CTRL+C and CMD+V/CTRL+V to copy and paste the workflow.)
It happens with any workflow that uses AI Agent Node and try to add Simple Memory.
When n8n runs in queue mode with multiple workers, Simple Memory is no longer suitable for production because it stores the conversation history only in the local in-process memory. In queue mode, each execution can land on a different worker, and n8n can’t guarantee that all calls to Simple Memory will hit the same worker.
The Simple Memory documentation is explicit about this:
“Don’t use this node if running n8n in queue mode. If your n8n instance uses queue mode, this node doesn’t work in an active production workflow. This is because n8n can’t guarantee that every call to Simple Memory will go to the same worker.”
So this isn’t treated as a bug but as an architectural limitation in multi-worker environments. Because the memory is in-memory and per worker, conversation context can disappear or become inconsistent between executions. For production or more advanced use cases, the AI memory docs recommend using persistent/shared memory backends such as Redis Chat Memory (optionally with TTL), Postgres Chat Memory, Xata, or Zep, which store state in a shared database/cache so all workers see the same history.
The documented workarounds are: run without queue mode (single process, where Simple Memory is safe again) or migrate to a persistent external memory (Redis/Postgres/Xata/Zep) when using queue mode to ensure consistent state across workers.
The best alternative is the Postgres Chat Memory node. Since you already have Postgres configured, this is the intended solution for your setup and will allow you to persist the memory correctly.
