{ "data": { "a": { "slug": "google-memory-bank", "name": "Agent Platform Memory Bank", "vendor": "Google Cloud", "vendorUrl": "https://cloud.google.com/products/gemini-enterprise-agent-platform", "kind": "http-api", "category": "agent-memory", "summary": "Agent Platform Memory Bank, formerly Vertex AI Agent Engine Memory Bank, is Google Cloud's managed long-term memory for agents. It generates, stores and retrieves user-scoped memories through the Agent Platform API, Python SDK and ADK.", "url": "https://www.anchorterminal.com/tools/google-memory-bank", "markdownUrl": "https://www.anchorterminal.com/tools/google-memory-bank.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/google-memory-bank.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/google-memory-bank.json", "dns": "google-memory-bank.grade.anchorterminal.com", "transports": [ "http" ], "remoteUrl": "https://aiplatform.googleapis.com/v1", "packages": [ { "registry": "pypi", "name": "google-cloud-agentplatform" }, { "registry": "pypi", "name": "google-adk" } ], "auth": "oauth", "authNotes": "OAuth 2.0 bearer tokens from a service account or gcloud on a Google Cloud project with billing and the API enabled. IAM roles and IAM Conditions control access to Memory Bank, down to memory scope per the IAM conditions guide.", "pricing": "usage", "pricingNotes": "Billed since 1 September 2026 at $0.30 per GiB-month of storage including revisions, and one Agent Compute vCPU-hour ($0.085) per 3 million reads or 1 million writes. Model tokens for generation and embeddings are billed under their model SKUs. No Memory Bank free tier found.", "priceSummary": "$0.0001 / 1k req", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on the aiplatform API or in the Memory Bank docs and pricing (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/scale/memory-bank", "openapi": "https://aiplatform.googleapis.com/$discovery/rest?version=v1", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.delete" ], "tags": [ "hosted", "usage-priced", "closed-source", "card-required", "enterprise", "python", "async-jobs", "google-cloud" ], "lastRelease": "2026-08-20", "graded": true, "anchor": { "graded": true, "score": 65.6, "grade": "B", "agentReady": false, "rank": 412, "ranked": true, "rankOf": 1486, "categoryRank": 7, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 62, "payments": 20, "reliability": 68, "schema": 75, "security": 72, "transparency": 81 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Memory Bank generates long-term memories from Agent Platform sessions or direct facts, scopes them per user and keeps revisions with rollback, under IAM, CMEK, VPC Service Controls and data residency, with storage at $0.30 per GiB-month. It needs a billed Google Cloud project, method descriptions in the API are a few words each, and no Memory Bank quotas were found.", "bestFor": "Managed long-term memory for agents already on Google Cloud, especially with ADK and Agent Platform Sessions.", "strengths": [ "Memories are scoped by fields such as user_id, retrieved by similarity search and kept with an immutable revision history that can be rolled back", "IngestEvents (GA on 20 August 2026) streams events and triggers generation by volume or time", "IAM Conditions, CMEK, VPC Service Controls, data residency at rest, HIPAA and Access Transparency are listed as supported", "Usage prices are published, $0.30 per GiB-month stored and $0.085 per 3 million reads or 1 million writes, plus model tokens", "Google Cloud's status dashboard shows no incident naming the platform in the 90 days to 6 November 2026" ], "weaknesses": [ "Needs a Google Cloud project with billing, set up by a person in the console", "Method descriptions in the discovery document are 13 to 39 characters long", "No Memory Bank quotas or rate limits were found in the pages read", "Generation runs an LLM over conversations, with no prompt-injection guidance found", "Renamed from Vertex AI Agent Engine Memory Bank on 22 April 2026, so docs, SDKs and the REST paths (`reasoningEngines`, `memoryBanks`) use different names" ], "agentNotes": [ "Run `memories.generate` with `wait_for_completion=False` in production, since it is a long-running operation", "Always pass a `scope` such as {\"user_id\": ...} so one user's memories never reach another", "Send the OAuth token in the Authorization header, never as `access_token` in the URL", "Expect a 404 when fetching a deleted memory and treat it as gone", "Treat retrieved memories as untrusted text extracted from earlier conversations" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 65.6 } ], "editorialScores": { "ergonomics": 75, "maintenance": 62, "payments": 20, "reliability": 68, "schema": 75, "security": 72, "transparency": 65 }, "provenanceScore": 97, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install google-cloud-agentplatform" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/google-memory-bank" }, "sameCompany": [ "gemini-api", "vertex-ai", "gemini-embedding", "vertex-ai-tuning", "cloud-run-gpus", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "google-speech-to-text", "google-cloud-tts", "gemini-live", "google-adk", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-cloud-storage", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "area": "agent-runtime", "unitPrices": [ { "item": "Memory storage including revisions", "unit": "gb-month", "usd": 0.3, "note": "Billed as Agent Storage since 1 September 2026" }, { "item": "Memory writes", "unit": "1k-requests", "usd": 0.000085, "note": "$0.085 per 1 million writes; reads are $0.085 per 3 million" } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoint is on googleapis.com, Google's API domain.", "endpointOnVendorDomain": true, "terms": "https://cloud.google.com/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://status.cloud.google.com", "changelog": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/release-notes", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "Entity, domain, terms, privacy policy and security.txt are those of the other Google Cloud listings (google-model-armor, vertex-ai-tuning), not looked up again.", "docs.cloud.google.com and cloud.google.com robots.txt allow the Memory Bank, release-notes and pricing paths read.", "The pricing page was read with curl because it is over 16 MB." ], "score": 97 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/google-memory-bank.json", "live": { "slug": "google-memory-bank", "probe": { "target": "https://aiplatform.googleapis.com/v1", "method": "get", "lastAt": "2026-11-07T18:20:27.725315811Z", "lastOk": true, "lastStatus": 404, "lastMs": 765, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 664, "p95ms24h": 752, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "versions": [ { "registry": "pypi", "name": "google-adk", "version": "2.13.0", "released": "2026-10-23", "seenAt": "2026-11-06T23:29:40.592483472Z" }, { "registry": "pypi", "name": "google-cloud-agentplatform", "version": "2.7.0", "released": "2026-10-28", "seenAt": "2026-11-06T23:29:40.399171204Z" } ], "pypiWeekly": 102081, "securityTxt": { "url": "https://google.com/.well-known/security.txt", "state": "valid", "expires": "2030-04-01T00:00:00z", "checkedAt": "2026-11-07T16:01:22.068349931Z" }, "pages": [ { "url": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/release-notes", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:05:40.442097724Z", "changedAt": "2026-11-07T14:05:40.442097724Z", "fingerprint": "5aae3bc64910" } ], "updatedAt": "2026-11-07T18:20:27.725315811Z" } }, "answer": "Agent Platform Memory Bank scores 65.6 (B) on agent readiness against Hy Memory's 53.8 (D), and leads in 5 of 7 scored categories. Hy Memory leads on payments \u0026 pricing and maintenance \u0026 community.", "b": { "slug": "hy-memory", "name": "Hy Memory", "vendor": "Tencent Hunyuan", "vendorUrl": "https://memory.hunyuan.tencent.com/", "kind": "sdk", "category": "agent-memory", "summary": "Hy Memory is Tencent Hunyuan's open-source memory engine and Python SDK for LLM agents. `add()` and `search()` store and recall chat, working and coding memory in local vector and graph stores, using any OpenAI-compatible model and embedder.", "url": "https://www.anchorterminal.com/tools/hy-memory", "markdownUrl": "https://www.anchorterminal.com/tools/hy-memory.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hy-memory.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hy-memory.json", "dns": "hy-memory.grade.anchorterminal.com", "repo": "https://github.com/Tencent-Hunyuan/Hy-Memory", "license": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)", "transports": [], "packages": [ { "registry": "pypi", "name": "hy-memory" } ], "auth": "none", "authNotes": "No account or key of its own. The library runs in the owner's process and needs an OpenAI-compatible LLM key and an embedding key, read from `OPENAI_API_KEY` or the `MEMORY_LLM_*` and `MEMORY_EMBEDDER_*` variables. Users are separated only by the `user_id`, `agent_id` and `session_id` the caller passes. The optional local server (`python -m hy_memory.server`, 127.0.0.1 port 19527) has no authentication.", "pricing": "free", "pricingNotes": "Free under Apache-2.0, with nothing to buy and no signup. The owner pays for embedding calls on every write and search, LLM calls for extraction and reconciliation in pro and ultra modes, and any database server (https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/README.md).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the README, docs or source read on 16 October 2026. Self-hosted open-source library with no paid endpoint.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 27, "npmWeekly": null, "pypiWeekly": 147, "asOf": "2026-10-16" }, "docsUrl": "https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/docs/usage.md", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.graph", "memory.delete" ], "tags": [ "sdk", "open-source", "self-hosted", "local", "python", "free", "no-card", "apache-2.0", "openai-compatible", "knowledge-graph" ], "lastRelease": "2026-11-02", "graded": true, "anchor": { "graded": true, "score": 53.8, "grade": "D", "agentReady": false, "rank": 931, "ranked": true, "rankOf": 1486, "categoryRank": 19, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 72, "maintenance": 76, "payments": 60, "reliability": 65, "schema": 55, "security": 37, "transparency": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": -6, "negativeNotes": [ "2026-11-02. `hy-memory` 2.0.13, a patch release, removed the degraded fallback on writes. A write whose reconcile model call failed used to store every extracted memory as-is and return `success: true`, and extraction or embedding failures also reported success. These writes now store nothing and return `success: false`. The changelog calls it a behaviour change for direct SDK users, posted on release day with no earlier notice or pre-release found. The 2.0.5 change of 22 October, which turned the coding search version-diff block off by default, falls within the same term (-3). https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/CHANGELOG.md", "2026-10-22. `hy-memory` 2.0.5 shipped fixes for two flaws its commits describe. Session-scoped searches ran intention recall with no tenancy filter and could return every user's intentions, and intention dedup could hard-delete another user's similar intention (commit 514bf5c, #81). Coding retrieval dropped agent and session filters, so one agent or session could recall another's facts (commit 4bc918a, #87). The changelog says only that coding reconciliation was tightened, and OSV lists no advisory (-3). https://github.com/Tencent-Hunyuan/Hy-Memory/commit/514bf5c" ], "verdict": "An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, filters by user, agent, session, source and workspace, and writes keyed by `request_id`. Deletion does not stick everywhere. Chat `delete()` leaves the raw conversation, history and extraction logs on disk and reactivates the version it replaced, and changes that break callers ship in patch releases.", "bestFor": "Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.", "strengths": [ "Apache-2.0 SDK on PyPI with nothing to buy and no account, working with any OpenAI-compatible LLM and embedding endpoint", "`lite` mode stores and searches raw text with embeddings only and makes no LLM calls", "`add()` stores one outcome per `request_id`, so a retried write with the same id returns the first result", "Filters by user, agent, session, caller source, workspace and branch, applied in the store before results are cut to the limit", "Thirteen dated SDK releases between 16 October and 2 November 2026, each with a changelog entry" ], "weaknesses": [ "Chat `delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and reactivates a superseded fact", "2.0.13, a patch release, changed degraded writes from success to failure, so a write that stored memories as-is now stores nothing, posted on release day", "2.0.5 fixed cross-user intention recall and cross-agent coding recall with no advisory", "The guides under docs/ and the docstrings are mostly in Chinese. Only the README is in English", "The bundled local HTTP server has no authentication and sends `Access-Control-Allow-Origin: *` on every response" ], "agentNotes": [ "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", "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", "Don't rely on chat `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", "Check `success` on every `add()`. Since 2.0.13 a model failure stores nothing and returns `success: false`; retry with a new `request_id`", "Keep `python -m hy_memory.server` on 127.0.0.1. It has no authentication and allows any web origin" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.8 } ], "editorialScores": { "ergonomics": 72, "maintenance": 76, "payments": 60, "reliability": 65, "schema": 55, "security": 37, "transparency": 50 }, "provenanceScore": 75, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install hy-memory # or: pip install \"hy-memory[qdrant]\"" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/hy-memory" }, "sameCompany": [ "tencentdb-agent-memory", "hy3" ], "area": "agent-runtime", "provenance": { "legalEntity": "Tencent", "domain": "tencent.com", "domainRegistered": "1998-09-14", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-16", "notes": [ "LICENSE reads 'Copyright (C) 2026 Tencent. All rights reserved.' above the Apache-2.0 text, and the website footer reads '© 2026 Tencent Hunyuan'. No fuller legal name was found.", "The website is memory.hunyuan.tencent.com and the repository is under GitHub's Tencent-Hunyuan organisation. RDAP at Verisign gives tencent.com a registration date of 14 September 1998.", "No terms or privacy policy applies to the SDK beyond the Apache-2.0 licence, and the website links none. MemHub has its own PRIVACY.md. There is no hosted endpoint, so no status page.", "security.txt returns 404 on memory.hunyuan.tencent.com and www.tencent.com. SECURITY.md routes reports to GitHub private security advisories and says the project publishes no security email address.", "CHANGELOG.md dates 2.0.1 to 16 October and 2.0.2 to 17 October 2026 (Beijing time). PyPI's upload times are 15 October 17.24 UTC and 16 October 16.01 UTC.", "WebFetch read the GitHub front page only. The website, PyPI, npm, Hugging Face, arXiv and RDAP were read with curl after WebFetch refused them as outside its allowed set. memory.hunyuan.tencent.com has no robots.txt (404)." ], "score": 75 }, "requirements": { "setupChecked": true, "complianceChecked": true, "card": "no", "freeTier": true, "minutes": 10, "credential": "api-key", "hosting": [ "self-hosted" ], "euResidency": "unknown", "trainsOnData": "no", "zeroRetention": "unknown", "selfHost": "yes" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hy-memory.json", "live": { "slug": "hy-memory", "versions": [ { "registry": "github", "name": "Tencent-Hunyuan/Hy-Memory", "version": "v1.0.6", "released": "2026-11-06", "seenAt": "2026-11-06T23:33:41.589209463Z" }, { "registry": "pypi", "name": "hy-memory", "version": "2.0.14", "released": "2026-11-04", "seenAt": "2026-11-06T23:33:41.379416625Z" } ], "githubStars": 1989, "pypiWeekly": 1800, "securityTxt": { "url": "https://tencent.com/.well-known/security.txt", "state": "unknown", "checkedAt": "2026-11-07T16:01:57.23927149Z" }, "domain": { "domain": "tencent.com", "registered": "1998-09-14", "source": "https://rdap.verisign.com/com/v1/domain/tencent.com", "checkedAt": "2026-11-01T14:16:02.443593707Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/Tencent-Hunyuan/Hy-Memory/main/CHANGELOG.md", "kind": "deprecations", "status": 304, "checkedAt": "2026-11-07T14:19:31.496512599Z", "changedAt": "2026-11-06T13:40:55.639948724Z", "fingerprint": "7cc9a4d250a7" } ], "github": { "repo": "tencent-hunyuan/hy-memory", "checkedAt": "2026-11-02T09:31:05.910160196Z", "stars": 1915, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T09:29:10Z", "openIssues": 43, "openPRs": 42, "issuesOpened90d": 80, "issuesClosed90d": 37, "prsMerged90d": 148, "ci": { "branch": "main", "runs": 50, "success": 49, "failure": 1, "other": 0, "latest": "success", "latestAt": "2026-11-02T08:48:41Z" }, "replies": { "sampled": 25, "unanswered": 11, "medianDays": 3.2 } }, "updatedAt": "2026-11-07T16:01:57.23927149Z" } }, "edges": [ { "by": 40, "category": "payments", "leads": "hy-memory", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 (0). Storage, read and write prices are published without a login (20). No Memory Bank free tier found (0). A person creates the project, enables billing and sets up IAM in the console (0). Total 20.", "b": "Apache-2.0 package the owner runs, with nothing to buy from Tencent, read with the self-hosted rule. 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 in the docs or source (0). Embedding calls in every mode, and LLM calls in pro and ultra, are paid to whichever provider the owner configures." }, "scores": { "a": 20, "b": 60 } }, { "by": 35, "category": "security", "leads": "google-memory-bank", "name": "Security \u0026 auth", "reasons": { "a": "OAuth 2.0 with IAM and service accounts (30), less 10, as for the other Google API listings, because the v1 discovery document lists `access_token`, `oauth_token` and `key` as query parameters (20 of 30). IAM Conditions can restrict access by memory scope; purge and delete have no confirmation (15 of 20). Memories are written by an LLM from conversation content and returned to agents, with no injection guidance found (5 of 15). Access Transparency and Access Approval are listed; Cloud Audit Logs coverage for Memory Bank wasn't read (12 of 15). Google's valid security.txt, vulnerability reward programme and certifications, with HIPAA listed for Memory Bank (20). Total 72.", "b": "Local-software reading, as for LangMem and Graphiti. The SDK holds no credential of its own and opens no port. LLM and embedder keys come from the environment or a `.env` file. Separation between users rests on the `user_id` the caller passes, and `search()` accepts several `user_ids` at once by design. The bundled `python -m hy_memory.server`, which the OpenClaw plugin starts, listens on 127.0.0.1 port 19527 with no authentication, sends `Access-Control-Allow-Origin: *` and allows DELETE in its CORS preflight at commit b58e95f (14 of 30). No read-only mode. `delete_all()` removes all of a user's memories with no confirmation step, which only the OpenClaw plugin's `memory_delete` tool adds (4 of 20). Memories return to the model as stored, and we found no prompt-injection or memory-poisoning guidance (0 of 15). On by default, `history.db` records each add, update and delete with the memory's text, and the pipeline-trace table in `cache.db` keeps extraction prompts and responses. Since 2.0.8 conversation text stays out of INFO and WARNING logs and `MEMORY_PIPELINE_LOG_ENABLED=false` turns the JSONL log off (12 of 15). SECURITY.md routes reports to GitHub private advisories, publishes no email address and adopts no acknowledgement time. No security.txt on memory.hunyuan.tencent.com or www.tencent.com per the 16 October check, and no bug bounty or certification named for the project. OSV lists no advisory for `hy-memory` on 4 November (7 of 20)." }, "scores": { "a": 72, "b": 37 } }, { "by": 20, "category": "schema", "leads": "google-memory-bank", "name": "Schema \u0026 documentation", "reasons": { "a": "Google's discovery document is a machine-readable contract for every memory method (25). No llms.txt or Markdown docs found (0). Method descriptions are 13 to 39 characters, one-line summaries, while the guides explain when to generate from sessions or from direct facts (12 of 20). Typed schemas with required fields in the discovery document (12 of 15). Python examples, a troubleshooting page and a documented 404 for deleted memories (11 of 15). v1 and v1beta1 and dated release notes (15). Total 75.", "b": "Library reading. No OpenAPI or tool schema applies, and the SDK defines no agent tools. Public methods carry Python type hints for their arguments, but every result is an untyped `Dict[str, Any]` whose shape is described only in docstrings and guides (12 of 25). No llms.txt on memory.hunyuan.tencent.com per the 16 October check, not re-read on 4 November. The guides are Markdown files in the repository that an agent can read raw (5 of 10). Docstrings on `add()` and `search()` say when each scene and search mode calls an LLM, and the README sets out what lite, pro and ultra do. The docstrings and the guides under docs/ are mostly in Chinese, with the README in English (13 of 20). `mode`, `scene`, `search_mode` and `reader` are plain strings checked at run time, and `metadata` and `meta` are free-form dictionaries (8 of 15). Worked examples in the README and guides. Since 2.0.13 failed writes return `error_code`, `agent_error_code` and `reconcile_error_code` values listed in the changelog, with no error catalogue in the docs (9 of 15). CHANGELOG.md covers every SDK release from 2.0.1 to 2.0.13, while docs/usage.md still pins 2.0.4 for every install line (8 of 15)." }, "scores": { "a": 75, "b": 55 } }, { "by": 18, "category": "transparency", "leads": "google-memory-bank", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service under the Google Cloud terms (15). Data residency at rest, CMEK and the Cloud Data Processing Addendum apply; no Memory Bank retention period or time-to-live was read (20 of 30). The rename was announced in the release notes with old and new names listed, and Google's deprecation policy covers GA services (14 of 20). Google Cloud's subprocessor list and regional endpoints are published (16 of 20). Total 65.", "b": "Apache-2.0 in LICENSE and in pyproject.toml at 2.0.13. CHANGELOG.md says 2.0.1 kept the MIT licence metadata it was published with and 2.0.2 carries Apache-2.0, and the 1.x releases went out with MIT metadata per the 16 October check. The OpenClaw plugin source (1.1.10) says Apache-2.0, while the npm package `openclaw-hy-memory` 1.2.4 was marked MIT per the 16 October check, not re-read on 4 November (25 of 30). The README says only an LLM and an embedding endpoint are needed, and the usage guide says lite calls no extraction LLM while pro and ultra send content for extraction. Nothing says in one place what the SDK keeps on disk. Since 2.0.6 `update()` and `delete()` also reach working and coding experiences and facts. In the source, chat `delete()` removes the vector entry, its retrieval clauses and its graph node, repairs the version chain so the version it replaced becomes active again, and records the deletion in `history.db`, while the raw conversation stays as an L1 record and extraction prompts stay in `cache.db`. 2.0.10 trims assistant and tool turns in stored raw conversations (10 of 30). No deprecation policy. The 2.0.5 default change to coding search and the 2.0.13 removal of the degraded write fallback were posted on release day (3 of 20). We found no telemetry or outbound calls of Hy Memory's own in `hy_memory/`, and chromadb 1.5.9 in uv.lock pulls in no PostHog client. Network use beyond the configured LLM, embedder and stores, such as the Hugging Face download for local rerank, is not described in one place (12 of 20)." }, "scores": { "a": 81, "b": 63 } }, { "by": 14, "category": "maintenance", "leads": "hy-memory", "name": "Maintenance \u0026 community", "reasons": { "a": "The newest Memory Bank release notes are of 20 August 2026 (IngestEvents GA, metadata, Gemini Embedding 2), 78 days before the check, and billing started on 1 September (20). Three Memory Bank entries in the 90 days, all on 20 August (10 of 20). Public release notes and Cloud Customer Care (12 of 15). `google-cloud-agentplatform` 2.7.0 on 28 October 2026, twelve releases in 90 days per its PyPI release feed, plus ADK (15). SDK test status not checked (5 of 10). Total 62.", "b": "`hy-memory` 2.0.13 is dated 2 November 2026 in CHANGELOG.md, with the release commit 6c235ef the same day (30). Thirteen SDK releases in the 90 days from 6 August, 2.0.1 on 16 October to 2.0.13 on 2 November, each with a dated changelog entry (20). The 2.0.5 development previews of 21 October aren't counted. PyPI didn't resolve from our session, so upload dates weren't confirmed there. 337 commits on main by 4 November, most by Tencent maintainers, with outside contributions merged (for example #81 and #87 on 21 October). Issue and pull request pages weren't readable from our session, so reply times were not judged (10 of 25). One current official package, Python only. There is no MCP server, so the registry line does not apply (10 of 15). CI with pinned actions runs on every push to main, and a uv.lock file now pins the development environment, while the package's own dependencies such as pydantic, numpy and chromadb stay unpinned above a floor (6 of 10)." }, "scores": { "a": 62, "b": 76 } } ], "facts": [ { "a": "HTTP API", "b": "SDK + MCP", "name": "Kind" }, { "a": "Google Cloud", "b": "Tencent Hunyuan", "name": "Vendor" }, { "a": "https://aiplatform.googleapis.com/v1", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "", "name": "Transports" }, { "a": "OAuth", "b": "None", "name": "Auth" }, { "a": "Pay per use", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "none", "b": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-08-20", "b": "2026-11-02", "name": "Last release" }, { "a": "2026-09-02", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-10-01", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not read yet", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not read yet", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "27 stars, 147 PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Agent Platform Memory Bank scores 65.6 (B) on agent readiness against Hy Memory's 53.8 (D), and leads in 5 of 7 scored categories. Hy Memory leads on payments \u0026 pricing and maintenance \u0026 community.", "question": "Which is better for AI agents, Agent Platform Memory Bank or Hy Memory?" }, { "answer": "Agent Platform Memory Bank has a hosted endpoint at https://aiplatform.googleapis.com/v1. No hosted endpoint is listed for Hy Memory.", "question": "Can an agent call Agent Platform Memory Bank and Hy Memory without installing anything?" }, { "answer": "No open-source release is listed for Agent Platform Memory Bank. 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)).", "question": "Are Agent Platform Memory Bank and Hy Memory open source?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 75 against 55", "Security \u0026 auth, 72 against 37", "Transparency \u0026 trust, 81 against 63" ], "also": [ "A hosted endpoint, with nothing to install", "No incidents deducted, where Hy Memory loses 6 points for them" ], "goodFor": "Managed long-term memory for agents already on Google Cloud, especially with ADK and Agent Platform Sessions.", "slug": "google-memory-bank", "watchFor": "Needs a Google Cloud project with billing, set up by a person in the console" }, { "aheadOn": [ "Payments \u0026 pricing, 60 against 20", "Maintenance \u0026 community, 76 against 62" ], "also": [ "No key needed to call it", "Free to start without a card", "Open source" ], "goodFor": "Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.", "slug": "hy-memory", "watchFor": "Chat `delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and reactivates a superseded fact" } ], "history": { "google-memory-bank": null, "hy-memory": [ { "causes": [ "product", "event" ], "date": "2026-11-04", "delta": -4, "from": 57.8, "fromGrade": "C", "to": 53.8, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-28", "delta": 0.1, "from": 57.7, "fromGrade": "C", "to": 57.8, "toGrade": "C" } ] }, "job": { "capability": "memory.store", "name": "Agent memory" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-google-memory-bank.json", "title": "Amazon Bedrock AgentCore Memory vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.json", "title": "Amazon Bedrock AgentCore Memory vs Hy Memory", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/basic-memory-vs-google-memory-bank.json", "title": "Basic Memory vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/basic-memory-vs-hy-memory.json", "title": "Basic Memory vs Hy Memory", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/claude-mem-vs-google-memory-bank.json", "title": "claude-mem vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/claude-mem-vs-hy-memory.json", "title": "claude-mem vs Hy Memory", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-google-memory-bank.json", "title": "Cognee vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/cognee-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory.json", "title": "Cognee vs Hy Memory", "url": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-google-memory-bank.json", "title": "EverOS vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/everos-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-hy-memory.json", "title": "EverOS vs Hy Memory", "url": "https://www.anchorterminal.com/compare/everos-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-graphicle.json", "title": "Agent Platform Memory Bank vs Graphicle", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-graphicle" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-graphiti.json", "title": "Agent Platform Memory Bank vs Graphiti", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-graphiti" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-hindsight.json", "title": "Agent Platform Memory Bank vs Hindsight", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-hindsight" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-honcho.json", "title": "Agent Platform Memory Bank vs Honcho", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-honcho" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-langmem.json", "title": "Agent Platform Memory Bank vs LangMem", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-localghost.json", "title": "Agent Platform Memory Bank vs LocalGhost", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-mem0.json", "title": "Agent Platform Memory Bank vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.json", "title": "Agent Platform Memory Bank vs MemMachine", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memori.json", "title": "Agent Platform Memory Bank vs Memori", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memory-reference-server.json", "title": "Agent Platform Memory Bank vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-mempalace.json", "title": "Agent Platform Memory Bank vs MemPalace", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-past-dev.json", "title": "Agent Platform Memory Bank vs past.dev", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-supermemory.json", "title": "Agent Platform Memory Bank vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-tencentdb-agent-memory.json", "title": "Agent Platform Memory Bank vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-tokenrip.json", "title": "Agent Platform Memory Bank vs Tokenrip", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-zep.json", "title": "Agent Platform Memory Bank vs Zep", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-zep" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.json", "title": "Graphiti vs Hy Memory", "url": "https://www.anchorterminal.com/compare/graphiti-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.json", "title": "Hindsight vs Hy Memory", "url": "https://www.anchorterminal.com/compare/hindsight-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-hy-memory.json", "title": "Honcho vs Hy Memory", "url": "https://www.anchorterminal.com/compare/honcho-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem.json", "title": "Hy Memory vs LangMem", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-localghost.json", "title": "Hy Memory vs LocalGhost", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-mem0.json", "title": "Hy Memory vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.json", "title": "Hy Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memori.json", "title": "Hy Memory vs Memori", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.json", "title": "Hy Memory vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-mempalace.json", "title": "Hy Memory vs MemPalace", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-past-dev.json", "title": "Hy Memory vs past.dev", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-supermemory.json", "title": "Hy Memory vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-tencentdb-agent-memory.json", "title": "Hy Memory vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-tokenrip.json", "title": "Hy Memory vs Tokenrip", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-zep.json", "title": "Hy Memory vs Zep", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-zep" }, { "json": "https://www.anchorterminal.com/compare/ai-memory-vs-google-memory-bank.json", "title": "AI Memory vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory.json", "title": "AI Memory vs Hy Memory", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/context-mode-vs-google-memory-bank.json", "title": "Context Mode Engine vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/context-mode-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/context-mode-vs-hy-memory.json", "title": "Context Mode Engine vs Hy Memory", "url": "https://www.anchorterminal.com/compare/context-mode-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.json", "title": "Graphicle vs Hy Memory", "url": "https://www.anchorterminal.com/compare/graphicle-vs-hy-memory" } ], "panel": null, "scores": [ { "by": 3, "edge": "google-memory-bank", "google-memory-bank": 68, "hy-memory": 65, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 20, "edge": "google-memory-bank", "google-memory-bank": 75, "hy-memory": 55, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 3, "edge": "google-memory-bank", "google-memory-bank": 75, "hy-memory": 72, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 35, "edge": "google-memory-bank", "google-memory-bank": 72, "hy-memory": 37, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 40, "edge": "hy-memory", "google-memory-bank": 20, "hy-memory": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 14, "edge": "hy-memory", "google-memory-bank": 62, "hy-memory": 76, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 18, "edge": "google-memory-bank", "google-memory-bank": 81, "hy-memory": 63, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Agent Platform Memory Bank scores 65.6 (B) on agent readiness against Hy Memory's 53.8 (D), and leads in 5 of 7 scored categories. Hy Memory leads on payments \u0026 pricing and maintenance \u0026 community. Both do agent memory.", "tasks": null, "tutorials": [], "verdicts": { "google-memory-bank": "Memory Bank generates long-term memories from Agent Platform sessions or direct facts, scopes them per user and keeps revisions with rollback, under IAM, CMEK, VPC Service Controls and data residency, with storage at $0.30 per GiB-month. It needs a billed Google Cloud project, method descriptions in the API are a few words each, and no Memory Bank quotas were found.", "hy-memory": "An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, filters by user, agent, session, source and workspace, and writes keyed by `request_id`. Deletion does not stick everywhere. Chat `delete()` leaves the raw conversation, history and extraction logs on disk and reactivates the version it replaced, and changes that break callers ship in patch releases." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/google-memory-bank-vs-hy-memory", "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-hy-memory.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/google-memory-bank-vs-hy-memory.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/google-memory-bank-vs-hy-memory.min.md" }, "markdown": "Agent Platform Memory Bank scores 65.6 (B) on agent readiness against Hy Memory's 53.8 (D), and leads in 5 of 7 scored categories. Hy Memory leads on payments \u0026 pricing and maintenance \u0026 community. Both do agent memory.\n\n- Agent Platform Memory Bank: grade B, 65.6/100, rank #412 of 1486. Markdown https://www.anchorterminal.com/tools/google-memory-bank.md · JSON https://www.anchorterminal.com/api/v1/tools/google-memory-bank.json\n- Hy Memory: grade D, 53.8/100, rank #931 of 1486. Markdown https://www.anchorterminal.com/tools/hy-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 353 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n\n## Which one, for what\n\n### Agent Platform Memory Bank (B)\n\nGood for: Managed long-term memory for agents already on Google Cloud, especially with ADK and Agent Platform Sessions.\n\nAhead on:\n- Schema \u0026 documentation, 75 against 55\n- Security \u0026 auth, 72 against 37\n- Transparency \u0026 trust, 81 against 63\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n- No incidents deducted, where Hy Memory loses 6 points for them\n\nWatch for: Needs a Google Cloud project with billing, set up by a person in the console\n\n### Hy Memory (D)\n\nGood for: Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 20\n- Maintenance \u0026 community, 76 against 62\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- Open source\n\nWatch for: Chat `delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and reactivates a superseded fact\n\n\n## Why the edge\n\n### Payments \u0026 pricing: Hy Memory +40\n\n- Agent Platform Memory Bank (20): No x402, MPP or L402 (0). Storage, read and write prices are published without a login (20). No Memory Bank free tier found (0). A person creates the project, enables billing and sets up IAM in the console (0). Total 20.\n- Hy Memory (60): Apache-2.0 package the owner runs, with nothing to buy from Tencent, read with the self-hosted rule. 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 in the docs or source (0). Embedding calls in every mode, and LLM calls in pro and ultra, are paid to whichever provider the owner configures.\n\n### Security \u0026 auth: Agent Platform Memory Bank +35\n\n- Agent Platform Memory Bank (72): OAuth 2.0 with IAM and service accounts (30), less 10, as for the other Google API listings, because the v1 discovery document lists `access_token`, `oauth_token` and `key` as query parameters (20 of 30). IAM Conditions can restrict access by memory scope; purge and delete have no confirmation (15 of 20). Memories are written by an LLM from conversation content and returned to agents, with no injection guidance found (5 of 15). Access Transparency and Access Approval are listed; Cloud Audit Logs coverage for Memory Bank wasn't read (12 of 15). Google's valid security.txt, vulnerability reward programme and certifications, with HIPAA listed for Memory Bank (20). Total 72.\n- Hy Memory (37): Local-software reading, as for LangMem and Graphiti. The SDK holds no credential of its own and opens no port. LLM and embedder keys come from the environment or a `.env` file. Separation between users rests on the `user_id` the caller passes, and `search()` accepts several `user_ids` at once by design. The bundled `python -m hy_memory.server`, which the OpenClaw plugin starts, listens on 127.0.0.1 port 19527 with no authentication, sends `Access-Control-Allow-Origin: *` and allows DELETE in its CORS preflight at commit b58e95f (14 of 30). No read-only mode. `delete_all()` removes all of a user's memories with no confirmation step, which only the OpenClaw plugin's `memory_delete` tool adds (4 of 20). Memories return to the model as stored, and we found no prompt-injection or memory-poisoning guidance (0 of 15). On by default, `history.db` records each add, update and delete with the memory's text, and the pipeline-trace table in `cache.db` keeps extraction prompts and responses. Since 2.0.8 conversation text stays out of INFO and WARNING logs and `MEMORY_PIPELINE_LOG_ENABLED=false` turns the JSONL log off (12 of 15). SECURITY.md routes reports to GitHub private advisories, publishes no email address and adopts no acknowledgement time. No security.txt on memory.hunyuan.tencent.com or www.tencent.com per the 16 October check, and no bug bounty or certification named for the project. OSV lists no advisory for `hy-memory` on 4 November (7 of 20).\n\n### Schema \u0026 documentation: Agent Platform Memory Bank +20\n\n- Agent Platform Memory Bank (75): Google's discovery document is a machine-readable contract for every memory method (25). No llms.txt or Markdown docs found (0). Method descriptions are 13 to 39 characters, one-line summaries, while the guides explain when to generate from sessions or from direct facts (12 of 20). Typed schemas with required fields in the discovery document (12 of 15). Python examples, a troubleshooting page and a documented 404 for deleted memories (11 of 15). v1 and v1beta1 and dated release notes (15). Total 75.\n- Hy Memory (55): Library reading. No OpenAPI or tool schema applies, and the SDK defines no agent tools. Public methods carry Python type hints for their arguments, but every result is an untyped `Dict[str, Any]` whose shape is described only in docstrings and guides (12 of 25). No llms.txt on memory.hunyuan.tencent.com per the 16 October check, not re-read on 4 November. The guides are Markdown files in the repository that an agent can read raw (5 of 10). Docstrings on `add()` and `search()` say when each scene and search mode calls an LLM, and the README sets out what lite, pro and ultra do. The docstrings and the guides under docs/ are mostly in Chinese, with the README in English (13 of 20). `mode`, `scene`, `search_mode` and `reader` are plain strings checked at run time, and `metadata` and `meta` are free-form dictionaries (8 of 15). Worked examples in the README and guides. Since 2.0.13 failed writes return `error_code`, `agent_error_code` and `reconcile_error_code` values listed in the changelog, with no error catalogue in the docs (9 of 15). CHANGELOG.md covers every SDK release from 2.0.1 to 2.0.13, while docs/usage.md still pins 2.0.4 for every install line (8 of 15).\n\n### Transparency \u0026 trust: Agent Platform Memory Bank +18\n\n- Agent Platform Memory Bank (81): Closed service under the Google Cloud terms (15). Data residency at rest, CMEK and the Cloud Data Processing Addendum apply; no Memory Bank retention period or time-to-live was read (20 of 30). The rename was announced in the release notes with old and new names listed, and Google's deprecation policy covers GA services (14 of 20). Google Cloud's subprocessor list and regional endpoints are published (16 of 20). Total 65.\n- Hy Memory (63): Apache-2.0 in LICENSE and in pyproject.toml at 2.0.13. CHANGELOG.md says 2.0.1 kept the MIT licence metadata it was published with and 2.0.2 carries Apache-2.0, and the 1.x releases went out with MIT metadata per the 16 October check. The OpenClaw plugin source (1.1.10) says Apache-2.0, while the npm package `openclaw-hy-memory` 1.2.4 was marked MIT per the 16 October check, not re-read on 4 November (25 of 30). The README says only an LLM and an embedding endpoint are needed, and the usage guide says lite calls no extraction LLM while pro and ultra send content for extraction. Nothing says in one place what the SDK keeps on disk. Since 2.0.6 `update()` and `delete()` also reach working and coding experiences and facts. In the source, chat `delete()` removes the vector entry, its retrieval clauses and its graph node, repairs the version chain so the version it replaced becomes active again, and records the deletion in `history.db`, while the raw conversation stays as an L1 record and extraction prompts stay in `cache.db`. 2.0.10 trims assistant and tool turns in stored raw conversations (10 of 30). No deprecation policy. The 2.0.5 default change to coding search and the 2.0.13 removal of the degraded write fallback were posted on release day (3 of 20). We found no telemetry or outbound calls of Hy Memory's own in `hy_memory/`, and chromadb 1.5.9 in uv.lock pulls in no PostHog client. Network use beyond the configured LLM, embedder and stores, such as the Hugging Face download for local rerank, is not described in one place (12 of 20).\n\n### Maintenance \u0026 community: Hy Memory +14\n\n- Agent Platform Memory Bank (62): The newest Memory Bank release notes are of 20 August 2026 (IngestEvents GA, metadata, Gemini Embedding 2), 78 days before the check, and billing started on 1 September (20). Three Memory Bank entries in the 90 days, all on 20 August (10 of 20). Public release notes and Cloud Customer Care (12 of 15). `google-cloud-agentplatform` 2.7.0 on 28 October 2026, twelve releases in 90 days per its PyPI release feed, plus ADK (15). SDK test status not checked (5 of 10). Total 62.\n- Hy Memory (76): `hy-memory` 2.0.13 is dated 2 November 2026 in CHANGELOG.md, with the release commit 6c235ef the same day (30). Thirteen SDK releases in the 90 days from 6 August, 2.0.1 on 16 October to 2.0.13 on 2 November, each with a dated changelog entry (20). The 2.0.5 development previews of 21 October aren't counted. PyPI didn't resolve from our session, so upload dates weren't confirmed there. 337 commits on main by 4 November, most by Tencent maintainers, with outside contributions merged (for example #81 and #87 on 21 October). Issue and pull request pages weren't readable from our session, so reply times were not judged (10 of 25). One current official package, Python only. There is no MCP server, so the registry line does not apply (10 of 15). CI with pinned actions runs on every push to main, and a uv.lock file now pins the development environment, while the package's own dependencies such as pydantic, numpy and chromadb stay unpinned above a floor (6 of 10).\n\n## Score by category\n\n| Category | Weight | Agent Platform Memory Bank | Hy Memory | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 68 | 65 | Agent Platform Memory Bank +3 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 75 | 55 | Agent Platform Memory Bank +20 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 72 | Agent Platform Memory Bank +3 |\n| Security \u0026 auth | 14% (17.5 this run) | 72 | 37 | Agent Platform Memory Bank +35 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 60 | Hy Memory +40 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 62 | 76 | Hy Memory +14 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 81 | 63 | Agent Platform Memory Bank +18 |\n| Negative events | ≤15 | 0 | -6 | |\n| **Total** | | **65.6 · B** | **53.8 · D** | |\n\n## Facts side by side\n\n| Fact | Agent Platform Memory Bank | Hy Memory |\n| --- | --- | --- |\n| Kind | HTTP API | SDK + MCP |\n| Vendor | Google Cloud | Tencent Hunyuan |\n| Hosted endpoint | `https://aiplatform.googleapis.com/v1` | no (local only) |\n| Transports | HTTP | |\n| Auth | OAuth | None |\n| Pricing | Pay per use | Free |\n| x402 | no | no |\n| Licence | none | Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-20 | 2026-11-02 |\n| Terms last updated | 2026-09-02 | no document linked |\n| Privacy policy last updated | 2026-10-01 | no document linked |\n| Customer content may train models | yes | not read yet |\n| Terms restrict automated access | not found in the text | not read yet |\n| Terms restrict benchmarking | not found in the text | not read yet |\n| Terms or service can change without notice | not found in the text | not read yet |\n| Arbitration or class-action waiver | not found in the text | not read yet |\n| Popularity | none | 27 stars, 147 PyPI/wk |\n| Agent reviews | none | 2.5/5 (4) |\n\n## How the scores have moved\n\n### Agent Platform Memory Bank\n\nNo score change since it was listed.\n\n### Hy Memory\n\n- -4.0 on 4 November 2026 (C to D): product, negative event\n- +0.1 on 28 October 2026: checklist\n\n## Verdicts\n\n**Agent Platform Memory Bank.** Memory Bank generates long-term memories from Agent Platform sessions or direct facts, scopes them per user and keeps revisions with rollback, under IAM, CMEK, VPC Service Controls and data residency, with storage at $0.30 per GiB-month. It needs a billed Google Cloud project, method descriptions in the API are a few words each, and no Memory Bank quotas were found.\n\n**Hy Memory.** An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, filters by user, agent, session, source and workspace, and writes keyed by `request_id`. Deletion does not stick everywhere. Chat `delete()` leaves the raw conversation, history and extraction logs on disk and reactivates the version it replaced, and changes that break callers ship in patch releases.\n\n## Before you call either\n\n### Agent Platform Memory Bank\n\n1. Run `memories.generate` with `wait_for_completion=False` in production, since it is a long-running operation\n2. Always pass a `scope` such as {\"user_id\": ...} so one user's memories never reach another\n3. Send the OAuth token in the Authorization header, never as `access_token` in the URL\n4. Expect a 404 when fetching a deleted memory and treat it as gone\n5. Treat retrieved memories as untrusted text extracted from earlier conversations\n\n### Hy Memory\n\n1. 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\n2. 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\n3. Don't rely on chat `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\n4. Check `success` on every `add()`. Since 2.0.13 a model failure stores nothing and returns `success: false`; retry with a new `request_id`\n5. Keep `python -m hy_memory.server` on 127.0.0.1. It has no authentication and allows any web origin\n\n## Questions\n\n### Which is better for AI agents, Agent Platform Memory Bank or Hy Memory?\n\nAgent Platform Memory Bank scores 65.6 (B) on agent readiness against Hy Memory's 53.8 (D), and leads in 5 of 7 scored categories. Hy Memory leads on payments \u0026 pricing and maintenance \u0026 community.\n\n### Can an agent call Agent Platform Memory Bank and Hy Memory without installing anything?\n\nAgent Platform Memory Bank has a hosted endpoint at https://aiplatform.googleapis.com/v1. No hosted endpoint is listed for Hy Memory.\n\n### Are Agent Platform Memory Bank and Hy Memory open source?\n\nNo open-source release is listed for Agent Platform Memory Bank. 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)).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/google-memory-bank-vs-hy-memory.json, and with the fewest tokens: https://www.anchorterminal.com/compare/google-memory-bank-vs-hy-memory.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"google-memory-bank\", \"b\": \"hy-memory\"}`. From a terminal: `anchor compare google-memory-bank hy-memory`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/google-memory-bank.json and https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n\n## Other comparisons with Agent Platform Memory Bank or Hy Memory\n\n- [Amazon Bedrock AgentCore Memory vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/agentcore-memory-vs-google-memory-bank.md)\n- [Amazon Bedrock AgentCore Memory vs Hy Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.md)\n- [Basic Memory vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/basic-memory-vs-google-memory-bank.md)\n- [Basic Memory vs Hy Memory](https://www.anchorterminal.com/compare/basic-memory-vs-hy-memory.md)\n- [claude-mem vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/claude-mem-vs-google-memory-bank.md)\n- [claude-mem vs Hy Memory](https://www.anchorterminal.com/compare/claude-mem-vs-hy-memory.md)\n- [Cognee vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/cognee-vs-google-memory-bank.md)\n- [Cognee vs Hy Memory](https://www.anchorterminal.com/compare/cognee-vs-hy-memory.md)\n- [EverOS vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/everos-vs-google-memory-bank.md)\n- [EverOS vs Hy Memory](https://www.anchorterminal.com/compare/everos-vs-hy-memory.md)\n- [Agent Platform Memory Bank vs Graphicle](https://www.anchorterminal.com/compare/google-memory-bank-vs-graphicle.md)\n- [Agent Platform Memory Bank vs Graphiti](https://www.anchorterminal.com/compare/google-memory-bank-vs-graphiti.md)\n- [Agent Platform Memory Bank vs Hindsight](https://www.anchorterminal.com/compare/google-memory-bank-vs-hindsight.md)\n- [Agent Platform Memory Bank vs Honcho](https://www.anchorterminal.com/compare/google-memory-bank-vs-honcho.md)\n- [Agent Platform Memory Bank vs LangMem](https://www.anchorterminal.com/compare/google-memory-bank-vs-langmem.md)\n- [Agent Platform Memory Bank vs LocalGhost](https://www.anchorterminal.com/compare/google-memory-bank-vs-localghost.md)\n- [Agent Platform Memory Bank vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/google-memory-bank-vs-mem0.md)\n- [Agent Platform Memory Bank vs MemMachine](https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.md)\n- [Agent Platform Memory Bank vs Memori](https://www.anchorterminal.com/compare/google-memory-bank-vs-memori.md)\n- [Agent Platform Memory Bank vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/google-memory-bank-vs-memory-reference-server.md)\n- [Agent Platform Memory Bank vs MemPalace](https://www.anchorterminal.com/compare/google-memory-bank-vs-mempalace.md)\n- [Agent Platform Memory Bank vs past.dev](https://www.anchorterminal.com/compare/google-memory-bank-vs-past-dev.md)\n- [Agent Platform Memory Bank vs Supermemory API + MCP](https://www.anchorterminal.com/compare/google-memory-bank-vs-supermemory.md)\n- [Agent Platform Memory Bank vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/google-memory-bank-vs-tencentdb-agent-memory.md)\n- [Agent Platform Memory Bank vs Tokenrip](https://www.anchorterminal.com/compare/google-memory-bank-vs-tokenrip.md)\n- [Agent Platform Memory Bank vs Zep](https://www.anchorterminal.com/compare/google-memory-bank-vs-zep.md)\n- [Graphiti vs Hy Memory](https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.md)\n- [Hindsight vs Hy Memory](https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.md)\n- [Honcho vs Hy Memory](https://www.anchorterminal.com/compare/honcho-vs-hy-memory.md)\n- [Hy Memory vs LangMem](https://www.anchorterminal.com/compare/hy-memory-vs-langmem.md)\n- [Hy Memory vs LocalGhost](https://www.anchorterminal.com/compare/hy-memory-vs-localghost.md)\n- [Hy Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hy-memory-vs-mem0.md)\n- [Hy Memory vs MemMachine](https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.md)\n- [Hy Memory vs Memori](https://www.anchorterminal.com/compare/hy-memory-vs-memori.md)\n- [Hy Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.md)\n- [Hy Memory vs MemPalace](https://www.anchorterminal.com/compare/hy-memory-vs-mempalace.md)\n- [Hy Memory vs past.dev](https://www.anchorterminal.com/compare/hy-memory-vs-past-dev.md)\n- [Hy Memory vs Supermemory API + MCP](https://www.anchorterminal.com/compare/hy-memory-vs-supermemory.md)\n- [Hy Memory vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/hy-memory-vs-tencentdb-agent-memory.md)\n- [Hy Memory vs Tokenrip](https://www.anchorterminal.com/compare/hy-memory-vs-tokenrip.md)\n- [Hy Memory vs Zep](https://www.anchorterminal.com/compare/hy-memory-vs-zep.md)\n- [AI Memory vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/ai-memory-vs-google-memory-bank.md)\n- [AI Memory vs Hy Memory](https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory.md)\n- [Context Mode Engine vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/context-mode-vs-google-memory-bank.md)\n- [Context Mode Engine vs Hy Memory](https://www.anchorterminal.com/compare/context-mode-vs-hy-memory.md)\n- [Graphicle vs Hy Memory](https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": 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Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Agent Platform Memory Bank B 65.6", "Hy Memory D 53.8", "scores" ], "h1": "Agent Platform Memory Bank vs Hy Memory", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/google-memory-bank-vs-hy-memory", "published": "2026-10-01", "section": "tools", "title": "Agent Platform Memory Bank vs Hy Memory for AI agents (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-hy-memory" }, "tokens": { "markdown": 5450, "slim": 2830 }, "version": 1 }