Memgraph

Overview

Memgraph is an in-memory graph database platform that features native vector search capabilities powered by USearch, a high-performance C++ library implementing the Hierarchical Navigable Small World (HNSW) index structure.

Key Features

• Native Vector Search: Built-in vector search using HNSW algorithm (since version 3.2)
• Single Platform: Combines graph database and vector search in one system
• Production Ready: Fully supported with CREATE VECTOR INDEX, persists across restarts
• High Performance: In-memory architecture for fast graph traversal and vector queries
• GraphRAG Support: Seamless integration of vector embeddings with knowledge graphs

Vector Search Implementation

Index Types

Memgraph supports single-store vector index on nodes where:

• Vector values stored only in the vector index backend (USearch)
• Property store keeps references (vector index IDs)
• Efficient memory utilization

Distance Metrics

Supports multiple similarity measures:

• Euclidean distance (L2)
• Cosine similarity
• Inner product

GraphRAG Applications

Memgraph enables powerful GraphRAG patterns by combining:

• Graph Database: Stores entities and relationships for multi-hop reasoning
• Vector Search: Semantic similarity matching for natural language queries
• Dynamic Updates: Real-time knowledge graph updates

Example Use Case: Biomedical Knowledge

• Store biomedical entities (genes, drugs, diseases) as graph nodes
• Vector embeddings for semantic search
• Relationship traversal for complex queries
• Multi-hop reasoning across connected entities

Use Cases

• RAG Systems: Retrieval based on semantic similarity + graph context
• Recommendation Engines: User-item matching with relational context
• Fraud Detection: Pattern recognition with relationship analysis
• Knowledge Discovery: Uncover hidden insights through graph connections
• Question Answering: Combine semantic search with knowledge graphs
• Research Tools: Link semantically similar concepts across domains

Integration

• Python client library
• Cypher query language (extended for vector operations)
• REST API
• Kafka, Pulsar streaming integrations
• LangChain compatibility for RAG workflows

Technical Specifications

• Storage: In-memory with optional disk persistence
• Query Language: Cypher with vector extensions
• Vector Index: HNSW via USearch
• Graph Processing: Native property graph model
• ACID Transactions: Full transactional support

Pricing

Memgraph offers:

• Open-source Community Edition (free)
• Enterprise Edition with advanced features
• Cloud-managed options

Contact sales for enterprise pricing details.