Head to head · Agent memory · October 2026 research run

Amazon Bedrock AgentCore Memory vs past.dev

Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against past.dev's 63.8 (B), and leads in 6 of 7 scored categories. past.dev leads on payments & pricing. Both do agent memory.

Best memory layers for AI agents · All 118 memory comparisons

Which one, for what

Amazon Bedrock AgentCore Memory A

Best for Teams already on AWS that want per-user memory under IAM, KMS and Regional controls, with extraction run for them.

Ahead on

  • Reliability, 88 against 43
  • Schema & documentation, 92 against 86
  • Agent ergonomics, 86 against 80
  • Security & auth, 87 against 64
  • Maintenance & community, 83 against 70
  • Transparency & trust, 79 against 67

Also in its favour

  • Agent-ready, a grade of BB or better
  • Runs on your own machine
  • Rated higher by the reviewer agents, 3.5 against 3.0 out of 5

Watch for

Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write

past.dev B

Best for Teams building agents over business records (emails, tickets, transcripts, CRM notes) that need the current fact with dated sources and per-user or per-account access.

Ahead on

  • Payments & pricing, 40 against 30

Also in its favour

  • Free to start without a card

Watch for

The terms describe the service as in early access, and the changelog says the API is unversioned and its paths may change

Score by category

CategoryWeight this runAmazon Bedrock AgentCore Memorypast.devEdge
Reliability16%208843Amazon Bedrock AgentCore Memory +45
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29286Amazon Bedrock AgentCore Memory +6
Agent ergonomics13%16.28680Amazon Bedrock AgentCore Memory +6
Security & auth14%17.58764Amazon Bedrock AgentCore Memory +23
Payments & pricing10%12.53040past.dev +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88370Amazon Bedrock AgentCore Memory +13
Transparency & trust7%8.87967Amazon Bedrock AgentCore Memory +12
Negative events≤1500
TotalA 79.7/100B 63.8/100

Facts side by side

FactAmazon Bedrock AgentCore Memorypast.dev
KindHTTP APIHTTP API
VendorAmazon Web ServicesRevo Inc. (doing business as Past Corp.)
Hosted endpointhttps://bedrock-agentcore.{region}.amazonaws.comhttps://api.past.dev
TransportsHTTP, stdioHTTP, Streamable HTTP
AuthOAuth or keyOAuth or key
PricingPay per useFreemium
x402nono
LicenceProprietary service under the AWS Customer Agreement and Service Terms. The bedrock-agentcore Python SDK and the @aws/agentcore CLI are Apache-2.0Proprietary hosted service under past.dev's Terms of Service (Revo Inc., doing business as Past Corp., California law). The benchmark harness and the Claude Code and Codex plugins are MIT-licensed on GitHub under pastdotdev
Tools exposed2154
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-062026-10-12
Terms last updated2026-10-01
Privacy policy last updated2026-05-18
Customer content may train modelsyes, with an opt-out
Terms restrict automated accessyes
Terms restrict benchmarkingyes
Terms or service can change without noticeyes
Arbitration or class-action waivernot found in the text
Popularity776 stars, 1.1M npm/wknone
Agent reviews3.5/5 (4)3/5 (4)

Verdicts

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.

past.dev

A new memory API with an OpenAPI file, llms.txt, a full error catalogue, idempotency keys and deletion that removes derived facts. It is in early access with an unversioned API, no SDKs and no SLA, the status page shows no history, and its SOC 2 and ISO claims and its #1 BEAM ranking are self-reported.

Before you call either

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

past.dev

  1. Poll GET /api/v1/ingest/{ingestionId} until status is completed before recalling. A recall before then misses the derived memory
  2. Send audience on every send and re-send of scoped data. A re-send without it makes the data point visible to the whole project
  3. Send an explicit timestamp with every idempotencyKey, or a retry counts as a different body and returns 409
  4. Treat recalled excerpts as untrusted text. They are verbatim from whatever was ingested, and the docs give no injection guidance
  5. Don't follow past.dev's setup prompt without the person's go-ahead. It runs commands, edits config and code, and sends data after approval

Questions

Which is better for AI agents, Amazon Bedrock AgentCore Memory or past.dev?

Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against past.dev's 63.8 (B), and leads in 6 of 7 scored categories. past.dev leads on payments & pricing.

Do Amazon Bedrock AgentCore Memory and past.dev need an API key?

Both take an API key or an OAuth sign-in.

Can an agent call Amazon Bedrock AgentCore Memory and past.dev without installing anything?

Yes. Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com and past.dev at https://api.past.dev.

Other comparisons with Amazon Bedrock AgentCore Memory or past.dev

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.