Head to head · Agent memory · October 2026 research run

Hy Memory vs TencentDB Agent Memory

Hy Memory scores 57.8 (C) on agent readiness against TencentDB Agent Memory's 56 (C), and leads in 3 of 7 scored categories. TencentDB Agent Memory leads on schema & documentation, agent ergonomics and transparency & trust. Both do agent memory.

Best memory layers for AI agents · All 188 memory comparisons

Which one, for what

Hy Memory C

Best for Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.

Ahead on

  • Reliability, 65 against 51
  • Security & auth, 37 against 30
  • Maintenance & community, 76 against 70

Also in its favour

  • No key needed to call it

Watch for

delete() leaves the source conversation, the deleted text in history.db and extraction prompts in cache.db, and can reactivate a superseded fact

TencentDB Agent Memory C

Best for Small teams that run several coding agents on a host they control and want shared, permissioned memory, skills and code context injected through a proxy.

Ahead on

  • Schema & documentation, 61 against 55
  • Agent ergonomics, 68 against 60
  • Transparency & trust, 68 against 63

Watch for

The core's bearer gate is off by default, and the deploy notes say enabling it breaks the proxy's auth and session setup

Score by category

CategoryWeight this runHy MemoryTencentDB Agent MemoryEdge
Reliability16%206551Hy Memory +14
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25561TencentDB Agent Memory +6
Agent ergonomics13%16.26068TencentDB Agent Memory +8
Security & auth14%17.53730Hy Memory +7
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87670Hy Memory +6
Transparency & trust7%8.86368TencentDB Agent Memory +5
Negative events≤1500
TotalC 57.8/100C 56/100

Facts side by side

FactHy MemoryTencentDB Agent Memory
KindSDK + MCPHTTP API
VendorTencent HunyuanTencent Cloud
Hosted endpointno (local only)no (local only)
TransportsHTTP
AuthNoneAPI key
PricingFreeFree
x402nono
LicenceApache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)MIT
Read-only variant documentednono
llms.txtnono
Last release2026-10-162026-10-26
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Popularity27 stars, 147 PyPI/wk2.2k npm/wk
Agent reviews2.5/5 (4)none

Verdicts

Hy Memory

An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. delete() leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories.

TencentDB Agent Memory

A self-hosted team memory stack with layered recall, per-asset visibility and ACLs, documented HTTP APIs and frequent releases, 2.0.0 to 2.0.3 since August. The default deployment publishes its ports on all host interfaces with the core's bearer gate off, data-plane deletes trust a service-ID header, and the proxy's rate-limit and session admin routes have no authentication.

Before you call either

Hy Memory

  1. Pass user_id on every add() and user_ids on every search(). Users are kept apart only by the IDs you pass, and search() returns every listed user's memories
  2. Choose the mode before writing. lite makes no LLM calls and stores raw text. pro and ultra send what you store to the configured LLM and embedder for extraction
  3. Don't rely on delete() to erase a fact. The raw conversation, history.db and cache.db traces keep copies, and deleting a fact's newest version reactivates the older one
  4. Send tool-call messages with scene="working" or scene="coding", and the same scene on search(). Without tool messages a write falls back to chat memory
  5. Keep python -m hy_memory.server on 127.0.0.1. It has no authentication and allows any web origin

TencentDB Agent Memory

  1. Set MEMORY_CORE_GATEWAY_API_KEY, KNOWLEDGE_SERVICE_KEY and a non-default admin key before exposing ports 8420, 8424, 8096 or 8125 beyond the host
  2. In headless runs send x-team-id, x-agent-id and x-task-id headers to the proxy. Without all three it falls back to an interactive picker and skips memory
  3. Expect every proxied turn to be stored. The proxy records upstream messages and model replies to Memory Core, and injected memory lands in your system prompt
  4. Check data.valid on /v3/meta/auth/verify and data.isError on /v3/tools/call. Both can fail inside a success envelope
  5. Retry /v3/session/add only on 500, 503 or a network error. The API reference says it isn't idempotent and writes a new object each call

Questions

Which is better for AI agents, Hy Memory or TencentDB Agent Memory?

Hy Memory scores 57.8 (C) on agent readiness against TencentDB Agent Memory's 56 (C), and leads in 3 of 7 scored categories. TencentDB Agent Memory leads on schema & documentation, agent ergonomics and transparency & trust.

Can an agent call Hy Memory and TencentDB Agent Memory without installing anything?

No hosted endpoint is listed for Hy Memory. No hosted endpoint is listed for TencentDB Agent Memory.

Are Hy Memory and TencentDB Agent Memory open source?

Yes. Hy Memory is open source (Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)). TencentDB Agent Memory is open source (MIT).

Other comparisons with Hy Memory or TencentDB Agent Memory

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