Memgraph
In-memory GraphRAG engine. Memgraph 3.0 adds native vector search alongside graph traversal. LangChain toolkit.
At a glance
- Type
- In-memory GraphRAG + native vector search
- Tier
- T2
- Section
- Knowledge-graph platforms
- Created
- 2016
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- Free + paid
- Funding
- $14M Seed · 2023-12
Taxonomy
- storage
- graph
- retrieval
- graph-traversal
- persistence
- session
- update
- overwrite
- unit
- fact
- governance
- inspectable
- conflict
- overwrite
When to use
Optimised for: relationship modeling + reasoning + governance over pure vector
Anti-fit: not for purely-vector or simple-RAG use cases (graph adds setup cost)
Pros & cons
Pros
In-memory graph DB optimized for real-time analytics; Cypher-compatible.
Cons
Smaller community than Neo4j; in-memory cost limits scale.
Claims & capabilities
Used by NASA and Cedars-Sinai for GenAI knowledge graphs.
Technical surface
- API surface
- Bolt, Cypher, SDK: many
- Backend storage
- custom (in-memory native graph)
- Deployment
- Both
- Embedding model
- BYO
- Multi-tenancy
- hard-isolation
- MCP
- via official adapter — Memgraph MCP
- A2A
- no Google A2A (Agent2Agent) integration documented as of 2026-05.
- OpenTelemetry
- first-class — Prometheus + OTel
Similar systems
Other knowledge-graph platforms in the catalog, ranked by inbound references.
- Neo4j T1
Property graph DB with Cypher; native vector search; Aura Agent + MCP server for graph-as-memory. $100M GenAI investment in 2025.
- Amazon Neptune Analytics T1
Vector index on graph nodes queryable via openCypher. Mem0 integration GA 2025; Cognee integration for agentic RAG. Combines semantic recall with multi-hop traversal in one managed service.
- AllegroGraph (Franz) T1
RDF triple/quad store with RDFS++ / OWL reasoning. v8.4 (May 2025) added an NLQ interface.
- Apache AGE T2
openCypher over Postgres. Pairs with pgvector for graph + vector hybrid retrieval. Azure Database for PostgreSQL ships AGE with ai_extension LLM functions for entity extraction directly in SQL.
- ArangoDB T1
HybridGraphRAG combines vector search, graph traversal, full-text in one AQL query. ArangoGraphML for ML pipelines; LangChain integration.
- Dgraph T2
Vector indexing on any node. Google Gen AI Toolbox integration; LangChain agent orchestration.
Related systems
References (1)
- LangChain (framework) integrates with — Memgraph 3.0 adds native vector search alongside graph traversal. LangChain toolkit.