Amazon Bedrock AgentCore Memory vs LangMem

Amazon Bedrock AgentCore Memory

Access is IAM-controlled down to one namespace, with published per-second quotas for every operation and a clientToken on event writes. Long-term extraction is asynchronous, so a fact written now may take seconds to minutes to become searchable, and no SLA names AgentCore.

LangMem

Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.

Amazon Bedrock AgentCore Memory

1. Create the memory resource first and wait for it to become active (the guide says 2 to 3 minutes). Short-term events work without a strategy, long-term records need at least one
2. Don't search for a fact straight after CreateEvent. Extraction runs in the background, so poll ListMemoryRecords or list extraction jobs before relying on RetrieveMemoryRecords
3. Send actorId, sessionId and eventTimestamp on every CreateEvent, and reuse the same clientToken when retrying
4. Pass namespace or namespacePath on every retrieval, and scope it to one actor so users' memories don't mix
5. Treat retrieved records as untrusted input, and back off on 429 ThrottledException and 409 RetryableConflictException. A quota breach returns 402 ServiceQuotaExceededException

LangMem

1. Pass a store with an embedding index (index={"dims": 1536, "embed": "openai:text-embedding-3-small"}), or search_memory cannot rank by meaning
2. Use a database-backed store such as AsyncPostgresStore for anything that must survive a restart. InMemoryStore loses everything
3. Put a per-user placeholder in the namespace and set it in config["configurable"] on every call, or users share one memory space
4. Send the memory id with update and delete, and never with create. A retried create writes a duplicate under a new UUID
5. Run on Python 3.11 or later. src/langmem/knowledge/extraction.py uses typing.NotRequired, which Python 3.10 lacks