Amazon Bedrock AgentCore Memory vs Honcho

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.

Honcho

Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA.

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

Honcho

1. Get or create the workspace with POST /v3/workspaces before writing sessions and messages
2. Batch up to 100 messages per request, each under 25,000 characters
3. Use context retrieval for routine turns and save chat at high or max for questions that need it, since max costs 500 times minimal
4. Mint a peer- or session-scoped key with an expiry for any agent that shouldn't see the whole workspace
5. Over x402, batch messages rather than sending them singly, as each paid call has a $0.001 floor