Google ADK Memory
https://google.github.io/adk-docs/sessions/memory/
Google's Agent Development Kit. Session services: InMemory / Database / VertexAI. Long-term: InMemoryMemoryService or VertexAIMemoryBankService (uses Vertex AI Memory Bank Preview for persistent cross-session memory).
At a glance
- Type
- SessionService tiers + VertexAIMemoryBank
- Tier
- T2
- Section
- Framework-embedded memory
- Created
- 2025-04 (launched at Google Cloud NEXT, April 9 2025)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- ADK OSS free; Vertex AI Memory Bank and Agent Engine: consumption-based pay-per-use cloud pricing (serverless); sta…
- Funding
- Google (subsidiary of Alphabet); no independent funding
Taxonomy
- storage
- kv
- retrieval
- injection
- persistence
- cross-session
- update
- overwrite
- unit
- episode
- governance
- inspectable
- conflict
- overwrite
When to use
Optimised for: Google Cloud / Vertex AI integration
Anti-fit: not for non-GCP stacks
Pros & cons
Pros
Google's Agent Development Kit with memory built in; integrates cleanly with Vertex AI Memory Bank.
Cons
Google-cloud-tilted; less idiomatic outside GCP.
Claims & capabilities
Two MemoryService implementations: InMemoryMemoryService (keyword search, dev/test) and VertexAiMemoryBankService (managed Google Cloud Memory Bank; default for Agent Platform Runtime). Memory Bank intelligently extracts and stores conversation events as long-term "memories" retrievable by semantic query
Technical surface
- API surface
- SDK: Python + Java (MemoryService, SessionService interfaces)
- Backend storage
- pluggable (Vertex AI Memory Bank)
- Deployment
- Both (ADK OSS self-hosted; one-command deploy to Google Cloud Agent Engine / Cloud Run / GKE)
- Embedding model
- multiple supported
- Multi-tenancy
- namespace
- MCP
- native (first-party) — ADK MCP integration
- A2A
- supported (native) — ADK is A2A reference impl
- OpenTelemetry
- first-class — Cloud Trace / OTel
Similar systems
Other framework-embedded memory in the catalog, ranked by inbound references.
- LangGraph Persistence T2
Distinct from LangMem. Built-in checkpointer saves graph state per super-step (short-term, thread-scoped). Store System adds long-term hierarchical key-value memory across threads with optional vector search + TTL. Postgres / Mongo / Redis stores for production.
- AutoGen Memory T2
ListMemory chronological context + teachable agents that vectorise corrections. Integrates with Mem0/Zep rather than building deep memory natively.
- CrewAI Memory T2
Memory subsystem inside the CrewAI orchestration framework; integrates with Mem0 for the long-term tier.
- AGiXT Adaptive Memory T2
Open-source AI automation platform. Routes between short-term and long-term memory adaptively across any LLM provider; plugin system for storage backends. Memory managed at the instruction-management layer — task context, instruction state, conversation history as unified agent state.
- Agno (Phidata) Memory T2
Agno (formerly Phidata). AgentStorage persists sessions to a DB; AgentMemory auto-classifies/store user preferences and conversation summaries. Single-line integrations with LanceDB, Pinecone, Weaviate, Qdrant.
- Botpress LLMz T1
Per-plan vector-DB storage quota + LLMz autonomous engine (in-session working memory) + Knowledge Base (semantic search over uploaded docs). Long-term user memory persists across sessions.